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Data science teams; Engineering teams; Product teams; Business stakeholders", "domainKnowledge" : "Cloud data stacks; ML frameworks; BI platforms; Statistical methods", "domainList" : [ "cloud-data-stacks", "ml-frameworks", "bi-platforms", "statistical-methods" ], "domainSpecificKnowledge" : [ "Cloud data stacks", "ML frameworks", "BI platforms", "Statistical methods" ], "toolProficiency" : [ "Dbt Cloud", "MLflow", "Snowflake", "BigQuery", "Databricks", "AWS SageMaker", "GCP Vertex AI", "Azure ML Studio" ], "qualificationsBasic" : "5+ years of experience in data engineering, Proficiency in SQL, Experience with Python", "qualificationsPreferred" : "Master's degree preferred, Experience with dbt Cloud, Experience with MLflow, Experience with Databricks, Experience with Snowflake, Experience with BigQuery, Experience with AWS SageMaker, Experience with GCP Vertex AI, Experience with Azure ML Studio, GCP Professional Data Engineer certification, AWS Data Analytics certification, Databricks Certified certification, Dbt Certified certification", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Velir is an established mid-sized agency with a top-tier portfolio of clients, ranging from the world’s largest non-profits to Fortune 500 brands. As of 2023, Velir acquired Brooklyn Data Company, a premier data and analytics consultancy focused on leadership, process improvement, implementation, and advanced analytics. At Velir, we believe people are our greatest asset. Our culture is built on a foundation of trust, collaboration, and continued improvement. We strive for excellence in everything we do, embracing challenges as opportunities for growth. Our success is driven by a shared passion for making a positive impact on our customers, our communities and each other. We are a remote first company that offers competitive pay and excellent benefits. Overview The Senior Data & Analytics Engineer will play a crucial role in helping our client organizations transform raw data into reliable, well-modeled assets that drive business decisions. This hybrid role bridges data engineering and analytics engineering — combining the infrastructure-building strengths of a data engineer with the transformation, modeling, and semantic layer expertise of an analytics engineer. Core responsibilities include Data Architecture Design, Data Modeling, ELT/ETL Development, Data Quality Assurance, and Scalability Optimization, with a strong emphasis on Databricks as the primary platform. Because our clients are mostly US-based organizations, we look for the ability to communicate with professional proficiency in English, verbally and in writing. Responsibilities Data & Analytics Engineering Expertise: You are responsible for building and maintaining the infrastructure and transformation layers that support the storing, movement, and modeling of data — enabling analysts, AI agents, and business stakeholders to confidently consume, interpret and take action. You will operate across both the data engineering and analytics engineering layers of the data stack, owning pipeline development and maintenance, as well as designing and building the resultant data models. Design, build, and maintain scalable data pipelines and ELT workflows, with Databricks as the primary platform Develop and maintain dbt models that are well-documented, tested, and structured for long-term maintainability Own data modeling decisions and methodology — defining entities, relationships, and grain — in collaboration with analytics and business stakeholders Consistently seek out and deliver on engagement-level vision, tasks, and problems Regularly delivers meaningful improvements to clients' data infrastructure and analytical capabilities Autonomous in approach and provides technical guidance to less experienced engineers Cross-Team Collaboration: You are responsible for collaborating with peers and other functional departments to develop and implement data strategies that support engagement goals and client needs. Collaborate with other data engineers and analytics engineers, data analysts, and clients on end-to-end data requirements Partner with clients and functional managers to plan for data engineering and modeling needs for product or feature launches Create processes and/or documentation templates that help cross-functional teams solve common data problems Drive data solution improvements that impact the client experience or empower internal stakeholders to do their jobs effectively Take initiative to identify, communicate, and solve important problems, coordinating with others on cross-cutting technical issues Project Delivery: You are responsible for ensuring that data engineering and analytics engineering projects are delivered on time, within scope, and within budget. Architect and design data systems and transformation layers using patterns that allow for iterative delivery and future scaling Proactively identify and address technical debt with careful evaluation of development cost Optimize for predictability and a regular cadence of deliverables Keep reliability, maintainability, and scalability of client systems top of mind Ability to identify and prioritize unowned or unglamorous work that enables the broader team to move faster Skills & Qualifications Proven experience as a Data Engineer, Analytics Engineer, or in a hybrid or generalist role, with a focus on designing and developing data pipelines and transformation layers Strong programming skills in Python and SQL Hands-on, deep expertise with Databricks — including Delta Lake, Unity Catalog, and Databricks workflows Strong proficiency with dbt for data transformation, testing, and documentation Demonstrated experience in data modeling — including dimensional modeling, entity-relationship design, and semantic layer development Deep knowledge of data warehousing and ELT/ETL processes Familiarity with data integration and orchestration platforms (e.g., Fivetran, Apache Airflow, Azure Data Factory) Experience with cloud platforms such as AWS, Azure, or Google Cloud Experience with other cloud data warehouses such as Snowflake or Motherduck is a plus Experience with streaming solutions such as Spark Streaming or Kafka is desirable but not required Familiarity with MLOps techniques and platforms is a plus but not required Strong analytical and problem-solving skills Excellent communication and collaboration skills Familiarity with leveraging coding assistants such as Claude Code, CoPilot, and/or Codex is a plus Physical Requirements Frequent sitting at a desk performing work on a computer Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions Compensation Range: $160,000 - 175,000 annually Please note that compensation packages are finalized after the interview process is concluded. We use a competency-based approach to base pay, which means it is based on the competencies and skills demonstrated for this role. Core Company Values Take the Long View - Ensure the company is built to last Be Courageous - Make the right decisions even when they aren't the easiest decisions Be Genuine - Bring honesty and authenticity to all that you do Work with Focus + Passion - Display purpose and pride in your work and never stop learning As an equal opportunity employer, we are firmly committing to diversity, equity, and inclusion in our hiring efforts. We recognize that we need team members from all backgrounds and experiences to successfully shape a positive employee experience as well as deliver our product and service solutions. To that end, we actively seek candidates who can bring diverse experiences and backgrounds to our team. We know that complex factors and systemic bias can get in the way of us meeting strong candidates, so please don't hesitate to apply even if you're not 100% sure. At this time, Velir does not sponsor candidates and unfortunately cannot accept those on OPT or CPT.", "summaryDescription" : "Senior Data and Analytics Engineer at Velir. Skills: Data engineering, Machine learning, Business intelligence, Analytics engineering. Design data pipelines. Build data models", "postedDate" : "2026-06-16T01:18:38.223", "createdAt" : "2026-06-16T01:18:38.223", "lastUpdated" : "2026-06-16T10:32:01.810", "ingestTimestamp" : "2026-06-16T01:18:38.223", "mongoId" : "6a307f57f292fd229c058281", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 160000, "salaryAnnualMax" : 175000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Data pipeline development", "Database management", "Cloud data platforms", "Machine learning models", "Statistical analysis", "A/B testing", "Causal inference", "Data engineering", "Machine learning", "Business intelligence", "Analytics engineering", "Data modeling", "ETL development", "Data warehousing", "Quantitative analysis", "AI development", "Cloud data stacks", "ML frameworks", "BI platforms", "Statistical methods", "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified", "Dbt Cloud", "MLflow", "Snowflake", "BigQuery", "Databricks", "AWS SageMaker", "GCP Vertex AI", "Azure ML Studio" ], "skillCount" : 32, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Senior", "dataQualityScore" : 1.0, "daysOld" : 0, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a3066fff292fd229cfb805a", "title" : "Manager, International Data and Strategy", "company" : "The National Football League", "industry" : "Sports & Fitness", "salary" : { "min" : 125000.0, "max" : 160000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "New York, New York, United States", "locations" : [ "New York", "New York", "United States" ], "certifications" : [ "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified" ], "timestamp" : "2026-06-16T11:06:39.308", "fingerprint" : "e94f06cfdc68def5c408265f1856d6fe9ae9b66f2e39878d1bcb2aa5fb6e5d61", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/nflcareers/jobs/5263067008", "externalId" : "5263067008", "industryFunction" : { }, "structuredLocations" : [ { "city" : "New York", "state" : "New York", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "40.7127281,-74.0060152" } ], "locationText" : "New York, New York, United States", "employmentType" : "FULL_TIME", "minimumEducation" : "Master's", "experienceMinYears" : 5, "experienceLevel" : "Manager", "technicalSkills" : "AWS Redshift, Adobe Marketing Suite, AEP, AEM, AJO, Power BI, Tableau", "professionalSkills" : [ "Data strategy", "Product ownership", "Technical leadership" ], "hardSkillsList" : [ "Data governance", "Data lakes", "Cloud data platforms", "Regression", "Classification", "Clustering", "Time-series analysis", "A/B testing", "Causal inference" ], "softSkillsList" : [ "Leadership", "Influencing" ], "hardSkills" : [ { "name" : "Data governance", "level" : "intermediate" }, { "name" : "Data lakes", "level" : "intermediate" }, { "name" : "Cloud data platforms", "level" : "intermediate" }, { "name" : "Regression", "level" : "intermediate" }, { "name" : "Classification", "level" : "intermediate" }, { "name" : "Clustering", "level" : "intermediate" }, { "name" : "Time-series analysis", "level" : "intermediate" }, { "name" : "A/B testing", "level" : "intermediate" }, { "name" : "Causal inference", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Influencing" } ], "majorSkills" : "Data strategy, Product ownership, Technical leadership", "majorSkillsList" : [ "Data strategy", "Product ownership", "Technical leadership" ], "coreResponsibilities" : "Develop data strategy, Own product roadmaps, Lead technical initiatives, Manage enterprise-scale data initiatives, Oversee cloud data platforms, Oversee data lakes, Oversee governance frameworks, Ensure privacy and compliance, Manage consent data, Engage senior leaders, Work with technical partners, Motivate teams", "teamCollaboration" : "Cross-functional teams; Matrixed organization", "domainKnowledge" : "Fan engagement; Lifecycle marketing", "domainList" : [ "fan-engagement", "lifecycle-marketing" ], "domainSpecificKnowledge" : [ "Fan engagement", "Lifecycle marketing" ], "toolProficiency" : [ "AWS Redshift", "Adobe Marketing Suite", "Power BI", "Tableau" ], "communicationSkills" : "Senior leader engagement; Technical partner communication", "specialRequirements" : "No relocation assistance", "qualificationsBasic" : "5+ years in data strategy, 5+ years in product ownership, 5+ years in technical leadership, Master’s degree or higher, SQL proficiency, 5+ years of experience", "qualificationsPreferred" : "Advanced degree preferred, Experience with privacy and compliance standards, Experience with GDPR/CCPA, Experience with consent data management, Knowledge of sports or fan-focused businesses, Understanding of fan engagement, Understanding of lifecycle marketing, Experience with AWS Redshift, Experience with Adobe Marketing Suite, Experience with AEP, Experience with AEM, Experience with AJO, Experience with Power BI, Experience with Tableau, GCP Professional Data Engineer certification, AWS Data Analytics certification, Databricks Certified certification, Dbt Certified certification", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "We are seeking a highly motivated Manager, International Data advanced degree preferred. 5+ years in data strategy, product ownership, or technical leadership roles. Exposure to enterprise-scale data initiatives, including cloud data platforms, data lakes, and governance frameworks. Experience with privacy and compliance standards, including GDPR/CCPA and consent data management, is preferred. Knowledge of sports or fan-focused businesses, including an understanding of fan engagement and lifecycle marketing, is an advantage. Proven experience working with AWS Redshift, Adobe Marketing Suite (AEP, AEM, AJO), BI Tools like Power BI, Tableau in a production environment is a plus. Demonstrated track record of collaborating across cross-functional teams and influencing decisions in a matrixed organization without direct reporting authority. Excellent communication skills with a demonstrated ability to engage senior leaders, work effectively with technical partners, and motivate teams to achieve high performance. Other Key Attributes / Characteristics Master’s degree or higher in statistics, data science, computer science, or other data related fields Terms / Expected Hours of Work Limited Travel Salary / Pay Range This job posting contains a pay range, which represents the range of salaries or hourly rates that the NFL believes, in good faith, at the time of this posting that it might be willing to pay for the posted job in the location(s) specified. The NFL expects to hire for this position near the middle of the range. Only in truly rare and exceptional circumstances, where an external candidate has experience, credentials or expertise that far exceed those required or expected for the position, would the NFL consider paying a salary or rate near the higher end of the range. Salary $125,000—$160,000 USD Benefits Information To learn more about our comprehensive benefits offerings, please visit: NFL BENEFITS At the NFL, in-person work at our offices is a top priority because it allows us to collaborate more effectively, build stronger connections, and maintain the culture that drives our success. This role requires onsite presence at an NFL office or stadium location, and remote and/or hybrid working options are not offered. NO RELOCATION ASSISTANCE WILL BE PROVIDED. The NFL is committed to building an inclusive work environment that reflects our incredible fan base. We provide an environment of mutual respect where equal employment opportunities are available to all employees and applicants without regard to status as protected by applicable federal, state, and local laws. WHO WE ARE: NFL Core Values: Respect: Everyone matters. We celebrate diverse opinions, honor hard work, and value every contribution. Integrity: We do what's right, even when it's tough. We hold ourselves accountable and always follow through. Team Responsibility: We support each other and our communities. No one is bigger than the game, and every action impacts others. Resiliency: We set high standards, overcome adversity, and adapt to challenges, always striving for excellence. NFL Leadership Attributes: Build Talent: We develop and nurture potential, empowering individuals to grow and succeed. Execute: We take action with precision, delivering results that drive our goals forward. Inspire: We motivate others through vision, energy, and a commitment to excellence. Live Our Values: We embody our core principles in every decision and action. Know the Business: We stay informed, understand our industry, and make decisions that strengthen our position. Think Big: We challenge the status quo, envision bold possibilities, and strive for transformative impact WHO YOU ARE: Talent Attributes: What we expect for our employees: Embody an enthusiastic, proactive can-do attitude Embrace grit, free from ego or entitlement Excel as a relationship builder, with the ability to influence Eager learner, driven by passion rather than just ambition Encompasses an incredible work ethic with an agile mindset", "summaryDescription" : "Manager, International Data and Strategy at The National Football League. Skills: Data strategy, Product ownership, Technical leadership. Develop data strategy. 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"dataQualityScore" : 1.0, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Sports", "llmIndustryConfidence" : 0.95 }, { "id" : "6a30794df292fd229c031216", "title" : "Director, Data and AI Engineering", "company" : "Benevity", "industry" : "Technology", "salary" : { "min" : 192000.0, "max" : 238810.0, "currency" : "CAD", "frequency" : "Yearly" }, "location" : "Toronto, Ontario", "locations" : [ "Toronto, Ontario" ], "certifications" : [ "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified" ], "timestamp" : "2026-06-16T15:07:30.375", "fingerprint" : "aaf0e33227ca131481be4962d98f3d416a3d9e7ac0a72837e11beccb51a05d5d", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/benevity/791ccf38-f164-4521-b05d-6f35fa1e7245/application", "externalId" : "791ccf38-f164-4521-b05d-6f35fa1e7245", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Toronto", "state" : "Ontario", "country" : "Canada", 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"Data-driven insights", "Self-service analytics", "Data pipelines", "Enterprise warehousing", "ML training", "Business reporting", "AI-powered features", "Anomaly detection", "Personalization", "Cost optimization", "MLOps", "CI/CD", "Real-time inference", "Recommendations", "Predictive analytics", "NLP", "Generative AI", "Ethical AI", "AI standards", "BI tools", "Dashboards", "Product analytics", "User behavior", "Feature engagement", "Embedded analytics", "SaaS metrics", "Data privacy", "Data security", "Compliance", "Data lineage", "Metadata management", "MDM", "RBAC", "ABAC", "ReBac", "Data sharing", "Data democratization", "Trusted data", "Documented data", "Team leadership", "Budget management", "Product innovations", "Multi-tenant SaaS", "Customer-facing analytics", "Emerging AI trends", "Responsible AI frameworks" ], "hardSkillsList" : [ "Regression", "Classification", "Clustering", "Time-series", "A/B testing", "Causal inference" ], "softSkillsList" : [ "Leadership" ], "hardSkills" : [ { "name" : "Regression", "level" : "intermediate" }, { "name" : "Classification", "level" : "intermediate" }, { "name" : "Clustering", "level" : "intermediate" }, { "name" : "Time-series", "level" : "intermediate" }, { "name" : "A/B testing", "level" : "intermediate" }, { "name" : "Causal inference", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" } ], "majorSkills" : "Data Engineering, AI/ML Engineering, Data Strategy, Business Intelligence", "majorSkillsList" : [ "Data Engineering", "AI/ML Engineering", "Data Strategy", "Business Intelligence" ], "coreResponsibilities" : "Define and execute data and AI strategy, Lead cross-functional teams, Establish data-as-a-product principles, Drive innovation in real-time analytics, Partner with Product, Engineering, and Customer Success teams, Design and oversee high-scale, cloud-native data architectures, Implement highly available, fault-tolerant data pipelines, Lead data modeling initiatives, Work with engineering teams to embed AI-powered features, Drive observability, monitoring, and cost optimization, Oversee the development of ML/AI models, Implement MLOps best practices, Lead initiatives in AI-powered recommendations, Ensure bias-free, ethical AI practices, Build and manage BI tools, Develop product analytics frameworks, Implement embedded analytics solutions, Optimize reporting for SaaS metrics, Own data governance frameworks, Define and implement data lineage, Drive role-based access controls, Champion data democratization", "teamCollaboration" : "Cross-functional teams; Product teams; Engineering teams; Customer Success teams", "projectManagementSkills" : [ "Agile" ], "domainKnowledge" : "B2B SaaS; Cloud-native architecture; Multi-tenant SaaS; SaaS metrics; GDPR; SOC 2; PIPEDA; CCPA", "domainList" : [ "b2b-saas", "cloud-native-architecture", "multi-tenant-saas", "saas-metrics", "gdpr", "soc-2", "pipeda", "ccpa" ], "domainSpecificKnowledge" : [ "B2B SaaS", "Cloud-native architecture", "Multi-tenant SaaS", "SaaS metrics", "GDPR", "SOC 2", "PIPEDA", "CCPA" ], "toolProficiency" : [ "Collibra", "Informatica", "Alation", "Immuta", "JIRA" ], "communicationSkills" : "Executive presentations; Technical documentation", "documentationSkills" : "Technical writing; API documentation; Architecture diagrams", "continuousLearning" : "Growth opportunities", "innovationCreativity" : "Innovation", "problemSolvingSkills" : "Root cause analysis; Troubleshooting", "qualificationsBasic" : "10+ years of experience in data engineering, AI/ML, or analytics leadership roles, SQL proficiency, Master's or PhD in", "qualificationsPreferred" : "PhD preferred, GCP Professional Data Engineer, AWS Data Analytics, Databricks Certified, Dbt Certified", "remoteFriendly" : true, "workSiteFlexibility" : "Flexible", "rawDescription" : "MEET BENEVITY Benevity is the way the world does good, providing companies (and their employees) with technology to take social action on the issues they care about. Through giving, volunteering, grantmaking, employee resource groups and micro-actions, we help most of the Fortune 100 brands build better cultures and use their power for good. We’re also one of the first B Corporations in Canada, meaning we’re as committed to purpose as we are to profits. We have people working all over the world, including Canada, Spain, Switzerland, the United Kingdom, the United States and more! We are seeking a Director of Data and ML/AI Engineering to lead our data and AI technology strategy, architecture, and execution within our B2B SaaS Benevity Impact Platform. This role is pivotal in enabling data-driven decision-making, product intelligence, and AI-powered services and automation across our platform. The ideal candidate will have deep expertise in scalable data engineering, AI/ML systems and services, and cloud-based data architectures, with a track record of building highly available, real-time analytics, and ML/AI-driven solutions for SaaS platforms. This role will oversee data science, data modeling, business intelligence, governance, and ML/AI systems engineering, ensuring alignment with our client and business needs. What you’ll do: Leadership & Data Strategy - Define and execute the data and AI strategy for our SaaS platform, ensuring alignment with business objectives and customer needs. - Lead cross-functional teams across data engineering, AI/ML, BI, and governance to deliver scalable, high-impact solutions. - Establish data-as-a-product principles, ensuring data assets are secure, reusable, and monetizable within our platform. - Drive innovation in real-time analytics, AI-powered automation and intelligence for clients. - Partner with Product, Engineering, and Customer Success teams to enhance data-driven insights, reporting, and self-service analytics. Data Engineering & Platform Architecture - Design and oversee high-scale, cloud-native data architectures that support real-time streaming, data lakes / lakehouses, and enterprise warehousing. - Implement highly available, fault-tolerant data pipelines to process, store, and serve insights across the platform. - Lead data modeling initiatives to optimize data structures for analytics, ML training, and business reporting. - Work with engineering teams to embed AI-powered features into the SaaS platform, enabling smart automation, anomaly detection, and personalization. - Drive observability, monitoring, and cost optimization across our cloud-based data infrastructure. AI/ML Engineering & Data Science - Oversee the development of ML/AI models, ensuring they are scalable, explainable, and deployed effectively in production. - Implement MLOps best practices, including CI/CD for models, versioning, and real-time inference. - Lead initiatives in AI-powered recommendations, predictive analytics, NLP, and generative AI to enhance our product offerings. - Ensure bias-free, ethical AI practices and compliance with industry AI standards and regulations. Business Intelligence & Product Analytics - Build and manage BI tools, dashboards, and self-service analytics to provide real-time insights to clients and internal stakeholders. - Develop product analytics frameworks, tracking user behavior, adoption, and feature engagement. - Implement embedded analytics solutions that allow clients to gain actionable insights from their data. - Optimize reporting for SaaS metrics (MRR, ARR, churn, retention, LTV, NPS) and drive data-informed decision-making. Data Governance & Compliance - Own data governance frameworks, ensuring data privacy, security, and compliance (GDPR, SOC 2, PIPEDA, CCPA, etc.). - Define and implement data lineage, metadata management, and master data management (MDM) best practices. - Drive role-based access controls (RBAC, ABAC or ReBac) and ensure secure, auditable data sharing within our SaaS ecosystem. - Champion data democratization, enabling teams to access trusted, well-documented data. What you’ll bring: - 10+ years of experience in data engineering, AI/ML, or analytics leadership roles, ideally in B2B SaaS or cloud-based platforms - Strong expertise in scalable data architectures, ML/AI systems, and embedded analytics - Proven track record in leading high-performance teams, managing budgets, and delivering data-driven product innovations - Experience with multi-tenant SaaS data governance, compliance (SOC 2, GDPR, etc.), and customer-facing analytics - Familiarity with emerging AI trends, including LLMs, Generative AI, and responsible AI frameworks - Familiarity with SaaS product analytics and AI-powered automation use cases - Master’s or PhD in Computer Science, Data Science, AI/ML, or a related field is preferred Technical Skills & Expertise - Data & AI Stacks (Cloud-Native, SaaS-Optimized) - Data Engineering & Storage: BigQuery, Redshift, Delta Lake, Snowflake, Databricks - AI/ML Frameworks: Azure AI, TensorFlow, PyTorch, Hugging Face, MLflow, Vertex AI - MLOps & Pipelines: Kubeflow, SageMaker, Airflow, Feature Stores, DataRobot - BI & Analytics Tools: Looker, Power BI, Mode Analytics, Amplitude, Mixpanel - Data Governance & Security: Collibra, Informatica, Alation, Immuta - Cloud & DevOps: AWS (S3, Lambda, Kinesis), GCP (BigQuery, Pub/Sub), Kubernetes, Terraform - Programming: Python, SQL, Scala, Java - Streaming & Real-Time Data: Kafka, Flink, Apache Beam DISCOVER YOUR PURPOSE AT WORK We’re not employees, we’re Benevity-ites. From all locations, backgrounds and walks of life, who deserve more … Innovative work. Growth opportunities. Caring co-workers. And a chance to do work that fills us with a sense of purpose. If the idea of working on tech that helps people do good in the world lights you up ... If you want a career where you’re valued for who you are and challenged to see who you can become … It’s time to join Benevity. We’re so excited to meet you. WHERE WE WORK At Benevity, we embrace a flexible hybrid approach to where we work that empowers our people in a way that supports great work, strong relationships, and personal well-being. For those located near one of our offices, while there’s no set requirement for in-office time, we do value the moments when coming together in person helps us build connection and collaboration. Whether it’s for onboarding, project work, or a chance to align and bond as a team, we trust our people to make thoughtful decisions about when showing up in person matters most. JOIN A COMPANY WHERE DEIB ISN’T A BUZZWORD Diversity, equity, inclusion and belonging are part of Benevity’s DNA. You’ll see the impact of our massive investment in DEIB daily — from our well-supported employee resources groups to the exceptional diversity on our leadership and tech teams. We know that diverse backgrounds, experiences, skills and passions are what move our business and our people forward, so we're committed to creating a culture of belonging with equal opportunities for everyone to shine. That starts with a fair and accessible hiring process. If you want to feel seen, heard and celebrated, you belong at Benevity. Candidates with disabilities who may require accommodations throughout the hiring or assessment process are encouraged to reach out to accommodations@benevity.com.", "summaryDescription" : "Director, Data and AI Engineering at Benevity. Skills: Data Engineering, AI/ML Engineering, Data Strategy, Business Intelligence. Define and execute data and AI strategy. 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Through giving, volunteering, grantmaking, employee resource groups and micro-actions, we help most of the Fortune 100 brands build better cultures and use their power for good. We’re also one of the first B Corporations in Canada, meaning we’re as committed to purpose as we are to profits. We have people working all over the world, including Canada, Spain, Switzerland, the United Kingdom, the United States and more! We are seeking a Director of Data and ML/AI Engineering to lead our data and AI technology strategy, architecture, and execution within our B2B SaaS Benevity Impact Platform. This role is pivotal in enabling data-driven decision-making, product intelligence, and AI-powered services and automation across our platform. The ideal candidate will have deep expertise in scalable data engineering, AI/ML systems and services, and cloud-based data architectures, with a track record of building highly available, real-time analytics, and ML/AI-driven solutions for SaaS platforms. This role will oversee data science, data modeling, business intelligence, governance, and ML/AI systems engineering, ensuring alignment with our client and business needs. What you’ll do: Leadership & Data Strategy - Define and execute the data and AI strategy for our SaaS platform, ensuring alignment with business objectives and customer needs. - Lead cross-functional teams across data engineering, AI/ML, BI, and governance to deliver scalable, high-impact solutions. - Establish data-as-a-product principles, ensuring data assets are secure, reusable, and monetizable within our platform. - Drive innovation in real-time analytics, AI-powered automation and intelligence for clients. - Partner with Product, Engineering, and Customer Success teams to enhance data-driven insights, reporting, and self-service analytics. Data Engineering & Platform Architecture - Design and oversee high-scale, cloud-native data architectures that support real-time streaming, data lakes / lakehouses, and enterprise warehousing. - Implement highly available, fault-tolerant data pipelines to process, store, and serve insights across the platform. - Lead data modeling initiatives to optimize data structures for analytics, ML training, and business reporting. - Work with engineering teams to embed AI-powered features into the SaaS platform, enabling smart automation, anomaly detection, and personalization. - Drive observability, monitoring, and cost optimization across our cloud-based data infrastructure. AI/ML Engineering & Data Science - Oversee the development of ML/AI models, ensuring they are scalable, explainable, and deployed effectively in production. - Implement MLOps best practices, including CI/CD for models, versioning, and real-time inference. - Lead initiatives in AI-powered recommendations, predictive analytics, NLP, and generative AI to enhance our product offerings. - Ensure bias-free, ethical AI practices and compliance with industry AI standards and regulations. Business Intelligence & Product Analytics - Build and manage BI tools, dashboards, and self-service analytics to provide real-time insights to clients and internal stakeholders. - Develop product analytics frameworks, tracking user behavior, adoption, and feature engagement. - Implement embedded analytics solutions that allow clients to gain actionable insights from their data. - Optimize reporting for SaaS metrics (MRR, ARR, churn, retention, LTV, NPS) and drive data-informed decision-making. Data Governance & Compliance - Own data governance frameworks, ensuring data privacy, security, and compliance (GDPR, SOC 2, PIPEDA, CCPA, etc.). - Define and implement data lineage, metadata management, and master data management (MDM) best practices. - Drive role-based access controls (RBAC, ABAC or ReBac) and ensure secure, auditable data sharing within our SaaS ecosystem. - Champion data democratization, enabling teams to access trusted, well-documented data. What you’ll bring: - 10+ years of experience in data engineering, AI/ML, or analytics leadership roles, ideally in B2B SaaS or cloud-based platforms - Strong expertise in scalable data architectures, ML/AI systems, and embedded analytics - Proven track record in leading high-performance teams, managing budgets, and delivering data-driven product innovations - Experience with multi-tenant SaaS data governance, compliance (SOC 2, GDPR, etc.), and customer-facing analytics - Familiarity with emerging AI trends, including LLMs, Generative AI, and responsible AI frameworks - Familiarity with SaaS product analytics and AI-powered automation use cases - Master’s or PhD in Computer Science, Data Science, AI/ML, or a related field is preferred Technical Skills & Expertise - Data & AI Stacks (Cloud-Native, SaaS-Optimized) - Data Engineering & Storage: BigQuery, Redshift, Delta Lake, Snowflake, Databricks - AI/ML Frameworks: Azure AI, TensorFlow, PyTorch, Hugging Face, MLflow, Vertex AI - MLOps & Pipelines: Kubeflow, SageMaker, Airflow, Feature Stores, DataRobot - BI & Analytics Tools: Looker, Power BI, Mode Analytics, Amplitude, Mixpanel - Data Governance & Security: Collibra, Informatica, Alation, Immuta - Cloud & DevOps: AWS (S3, Lambda, Kinesis), GCP (BigQuery, Pub/Sub), Kubernetes, Terraform - Programming: Python, SQL, Scala, Java - Streaming & Real-Time Data: Kafka, Flink, Apache Beam DISCOVER YOUR PURPOSE AT WORK We’re not employees, we’re Benevity-ites. From all locations, backgrounds and walks of life, who deserve more … Innovative work. Growth opportunities. Caring co-workers. And a chance to do work that fills us with a sense of purpose. If the idea of working on tech that helps people do good in the world lights you up ... If you want a career where you’re valued for who you are and challenged to see who you can become … It’s time to join Benevity. We’re so excited to meet you. WHERE WE WORK At Benevity, we embrace a flexible hybrid approach to where we work that empowers our people in a way that supports great work, strong relationships, and personal well-being. For those located near one of our offices, while there’s no set requirement for in-office time, we do value the moments when coming together in person helps us build connection and collaboration. Whether it’s for onboarding, project work, or a chance to align and bond as a team, we trust our people to make thoughtful decisions about when showing up in person matters most. JOIN A COMPANY WHERE DEIB ISN’T A BUZZWORD Diversity, equity, inclusion and belonging are part of Benevity’s DNA. You’ll see the impact of our massive investment in DEIB daily — from our well-supported employee resources groups to the exceptional diversity on our leadership and tech teams. We know that diverse backgrounds, experiences, skills and passions are what move our business and our people forward, so we're committed to creating a culture of belonging with equal opportunities for everyone to shine. That starts with a fair and accessible hiring process. If you want to feel seen, heard and celebrated, you belong at Benevity. Candidates with disabilities who may require accommodations throughout the hiring or assessment process are encouraged to reach out to accommodations@benevity.com.", "summaryDescription" : "Director, Data and AI Engineering at Benevity", "createdAt" : "2026-06-16T00:25:36.052", "lastUpdated" : "2026-06-16T11:55:49.932", "ingestTimestamp" : "2026-06-16T00:25:36.052", "mongoId" : "6a3074d9f292fd229c009d20", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "150k-200k", "hasSalary" : false, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Director", "dataQualityScore" : 0.7777778, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "SaaS", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2c957a74d8ee00a098d2de", "title" : "CRM and Data Manager", "company" : "DIM Brands International", "industry" : "Retail", "salary" : { "min" : 65000.0, "max" : 95000.0, "currency" : "EUR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Manager in Retail in Rueil-Malmaison, France, adjusted for seniority and company size." }, "location" : "DIM", "locations" : [ "DIM" ], "timestamp" : "2026-06-15T10:19:28.809", "fingerprint" : "f05a02a872fa9bbf998c777d4bd011e4d6e7f569d770000a0b2c45630039132c", "source" : "greenhouse", "language" : "fr", "applyUrl" : "https://job-boards.greenhouse.io/dim/jobs/8002978", "externalId" : "8002978", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Rueil-Malmaison", "country" : "France", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "48.8777800,2.1802832" } ], "locationText" : "Rueil-Malmaison, France", "employmentType" : "FULL_TIME", "experienceLevel" : "Manager", "technicalSkills" : "CRM, Data management, Customer Data Platform, IA", "professionalSkills" : [ "Customer engagement", "Customer retention", "Customer satisfaction", "Omnichannel approach", "Data analysis", "Reporting", "Process optimization" ], "hardSkillsList" : [ "Data quality monitoring", "Performance tracking", "KPI reporting", "Customer service management" ], "hardSkills" : [ { "name" : "Data quality monitoring", "level" : "intermediate" }, { "name" : "Performance tracking", "level" : "intermediate" }, { "name" : "KPI reporting", "level" : "intermediate" }, { "name" : "Customer service management", "level" : "intermediate" } ], "majorSkills" : "CRM, Data Management, Customer Experience, Team Leadership", "majorSkillsList" : [ "CRM", "Data Management", "Customer Experience", "Team Leadership" ], "coreResponsibilities" : "Pilot engagement plans, Pilot retention plans, Pilot satisfaction plans, Supervise campaign implementation, Supervise customer journeys, Supervise activation scenarios, Coordinate CRM program redesign, Coordinate CRM program optimization, Ensure targeting relevance, Ensure database exploitation, Monitor data quality, Identify data anomalies, Track performance, Update key dashboards, Report regularly to management, Share best practices, Share campaign results, Manage collaborators daily, Help collaborators upskill, Track collaborator planning, Resolve daily issues, Supervise European customer service, Optimize response processes, Ensure tool configuration", "teamCollaboration" : "IT teams; E-commerce teams; Retail teams; European countries", "domainKnowledge" : "Retail; E-commerce", "domainList" : [ "retail", "e-commerce" ], "domainSpecificKnowledge" : [ "Retail", "E-commerce" ], "toolProficiency" : [ "Klaviyo", "Gladly" ], "innovationCreativity" : "Propose new ideas; Propose new tools", "problemSolvingSkills" : "Identify anomalies; Resolve issues", "outcomesObjectives" : "Measure action impact", "qualificationsBasic" : "8 to 10 years experience, Management experience, Comfortable with numbers, Understand database functioning, Rigorous, Proficient in campaign management tools, Proficient in customer service tools, Fluent English", "qualificationsPreferred" : "Retail or e-commerce experience", "workSiteFlexibility" : "Flexible", "rawDescription" : "DIM Brands International (DBI) est un fabricant et distributeur éco-responsable de sous-vêtements des marques parmi les plus fortes au monde (DIM, Nur Die, Lovable, La Senza...) pour toute la famille. DIM est le leader du marché en France et la marque préférée des consommateurs français (Étude OpinionWay – 1059 répondants – février 2025), Nur Die est le leader du marché en Allemagne dans le segment des produits de consommation, Lovable est un solide second sur le marché italien de la lingerie et La Senza est une marque canadienne emblématique de sous-vêtements. Les produits DIM sont distribués en Omnicanalité (GMS, Ecommerce et Boutiques DIM). Fondée en 1960, DBI a une longue tradition d'innovation et d'excellence. En 2022, l'entreprise a retrouvé son indépendance et entend accélérer sa croissance en s'appuyant sur une stratégie claire basée sur quatre axes : le développement de ses marques phares, un solide programme d'innovations produits, une stratégie omnicanale forte et un programme d'excellence opérationnelle continue. \"Simplification and Scale\" est notre devise stratégique. Notre ambition est d'ouvrir un nouveau cycle de croissance rentable et de réaliser le plein potentiel mondial de la marque DIM. Le siège de DBI est situé à Rueil-Malmaison, près de Paris, avec des filiales dans toute l'Europe (DACH, Italie, Ibérie, Europe de l'Est, Canada) et des distributeurs au Moyen-Orient, en Asie et en Afrique. Son centre d'approvisionnement (fabrication et logistique) est basé à Autun, en Bourgogne, où plus de 5 milliards de collants ont été produits depuis la création de DIM ! De plus, nous sommes profondément engagés dans une stratégie dynamique ESG, structurée autour de 3 piliers : Planète, Produit, Personnes. Par exemple, la marque DIM est neutre en CO2 scope 1&2, grâce à un mix de réduction et de capture des émissions. Dans ce contexte, la direction e-commerce recrute un CRM and Data Manager en CDI. Contexte & Enjeux Sous la responsabilité de la Directrice E-commerce, vous pilotez les plans d'actions d’engagement, de fidélisation et de satisfaction client de nos différentes marques (Dim, Playtex, Abanderado, Lovable….). Le poste est basé en France (siège), d'où vous coordonnez le périmètre européen. À la tête d'une équipe de 2 personnes (un(e) Responsable CRM et un(e) Responsable Service Client), et en étroite collaboration avec les équipes IT, E-commerce et Retail, vous veillez à la cohérence de l'expérience client depuis le premier contact jusqu'au service après-vente. Manager de proximité, vous aimez le travail en équipe et apportez votre soutien opérationnel à vos collaborateurs en maîtrisant les outils du quotidien. Vos Missions Animation & Déploiement CRM / Fidélisation Superviser et accompagner la mise en œuvre opérationnelle des campagnes, des parcours clients (approche omnicanale) et des scénarios d'activation. Coordonner les projets de refonte ou d'optimisation des programmes CRM pour nos marques en Europe, en lien avec les équipes IT, E-commerce et Retail. Garantir la pertinence des ciblages et la bonne exploitation de la base de données clients (Customer Data Platform) en collaboration avec l'IT. Amélioration continue : Assurer une veille sur les bonnes pratiques du marché et proposer de nouvelles idées ou outils simples (nouveaux canaux, IA d'aide à la rédaction, etc.) pour moderniser nos pratiques. Faire évoluer le programme de fidélité de DIM France et optimiser les scénarios d’automation. Suivi des données & Reporting Suivi de la qualité de la donnée : vous comprenez les flux de données pour repérer les anomalies simples (problèmes d'import, écarts de chiffres, bugs outils) et faites le lien avec les équipes IT pour leur résolution. Suivre la performance : Suivre et mettre à jour les dashboards clés (KPIs d'engagement, conversion, rétention, NPS) pour mesurer l'impact des actions. Partage des résultats : Assurer un reporting régulier auprès de la direction et des pays pour partager les bonnes pratiques et les résultats des campagnes. Management, Support Outils & Service Client Manager et accompagner au quotidien vos 2 collaborateurs : vous les aidez à monter en compétences, suivez leur planning et débloquez avec eux les sujets du quotidien sur les outils (Klaviyo, Gladly, etc.). Superviser le Service Client européen (géré opérationnellement par votre collaborateur), en l'aidant à optimiser les process de réponse et à s'assurer du bon paramétrage de l'outil de ticketing. Profil recherché Expérience : 8 à 10 ans d'expérience en CRM, marketing relationnel ou expérience client, idéalement dans l'univers du retail ou du e-commerce. Management & Posture : Vous avez une première expérience de management et un tempérament de \"facilitateur\". Vous aimez être proche de votre équipe et l'aider concrètement sur le terrain. Sensibilité Tech & Data : Vous êtes à l'aise avec les chiffres et comprenez le fonctionnement d'une base de données. Vous êtes rigoureux(se) et savez repérer quand \"un chiffre ne colle pas\" dans un outil. Compétences outils : Vous avez une bonne maîtrise pratique des outils de gestion de campagne (idéalement Klaviyo) et de service client (Gladly ou équivalent). Qualités personnelles : Forte orientation client, rigueur, bon relationnel pour travailler avec des interlocuteurs variés (IT, Retail, pays). Langues : Anglais courant indispensable pour échanger avec nos interlocuteurs internes et prestataires. Le poste est basé à Rueil-Malmaison dans des locaux au bord de la Seine. Life @DIM : Les collaborateurs sont mis au cœur de la stratégie de l’entreprise, ce qui vous permet d'obtenir les avantages suivants : Évoluer au sein d’un environnement stimulant parmi une équipe jeune et dynamique, et relever de nouveaux défis chaque jour Profiter du restaurant d'entreprise Avoir accès aux ventes organisées par le CE et 30% de réduction sur les produits de nos boutiques et sites internet Avoir un accès à la Conciergerie (services proposés par des esthéticiennes, ostéopathes, cordonniers…) Coaching sportif", "summaryDescription" : "CRM and Data Manager at DIM Brands International. Skills: CRM, Data Management, Customer Experience, Team Leadership. Pilot engagement plans. Pilot retention plans", "postedDate" : "2026-06-14T09:40:26.019", "createdAt" : "2026-06-14T09:40:26.019", "lastUpdated" : "2026-06-15T10:19:28.809", "ingestTimestamp" : "2026-06-14T09:40:26.019", "mongoId" : "6a2c957a74d8ee00a098d2de", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "50k-75k", "hasSalary" : false, "allSkills" : [ "Data quality monitoring", "Performance tracking", "KPI reporting", "Customer service management", "CRM", "Data Management", "Customer Experience", "Team Leadership", "Customer engagement", "Customer retention", "Customer satisfaction", "Omnichannel approach", "Data analysis", "Reporting", "Process optimization", "Retail", "E-commerce", "Klaviyo", "Gladly" ], "skillCount" : 19, "jobCategory" : "marketing", "jobSubcategory" : "growth", "seniorityLevel" : "Manager", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Retail", "llmIndustryConfidence" : 0.95 }, { "id" : "6a3087a4f292fd229c08b1f8", "title" : "Business Analyst, Data Masking and Compliance", "company" : "Capco", "industry" : "Consulting", "salary" : { "min" : 118000.0, "max" : 152000.0, "currency" : "CAD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Canada - Toronto", "locations" : [ "Canada - Toronto" ], "timestamp" : "2026-06-16T12:32:44.174", "fingerprint" : "f519232f48132c719665d37d19932956dfa1532fec2df391bf8a340f99776803", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/capco/jobs/8003346", "externalId" : "8003346", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Toronto", "state" : "Ontario", "country" : "Canada", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "43.6534817,-79.3839347" } ], "locationText" : "Toronto, Ontario, Canada", "employmentType" : "FULL_TIME", "professionalSkills" : [ "Data governance", "Risk remediation", "Stakeholder management", "Data analysis", "Process design", "Process engineering", "Operational improvement" ], "hardSkillsList" : [ "Data masking standards", "Evidence collection", "Compliance reporting", "Governance metrics" ], "hardSkills" : [ { "name" : "Data masking standards", "level" : "intermediate" }, { "name" : "Evidence collection", "level" : "intermediate" }, { "name" : "Compliance reporting", "level" : "intermediate" }, { "name" : "Governance metrics", "level" : "intermediate" } ], "majorSkills" : "Data masking, Compliance, Risk remediation, Data governance", "majorSkillsList" : [ "Data masking", "Compliance", "Risk remediation", "Data governance" ], "coreResponsibilities" : "Assess applications against data masking standards, Identify compliance gaps, Identify remediation requirements, Partner with application owners, Understand application processes, Understand data flows, Understand masking requirements, Design evidence collection processes, Implement evidence collection processes, Demonstrate compliance through objective testing, Facilitate stakeholder discussions, Align business requirements with standards, Support adoption of required controls, Create compliance reporting, Track status, Generate governance metrics", "teamCollaboration" : "Partnering with stakeholders; Bridging business and technology teams; Application owners; Business stakeholders; Senior stakeholders", "projectManagementSkills" : [ "Audit remediation" ], "domainKnowledge" : "Data masking; Data governance; Banking; Payments; Enterprise technology; Risk management; Operational risk", "domainList" : [ "data-masking", "data-governance", "banking", "payments", "enterprise-technology", "risk-management", "operational-risk" ], "domainSpecificKnowledge" : [ "Data masking", "Data governance", "Banking", "Payments", "Enterprise technology", "Risk management", "Operational risk" ], "communicationSkills" : "Stakeholder communication", "continuousLearning" : "Professional development; Industry-leading expertise", "problemSolvingSkills" : "Translating standards; Practical requirements", "outcomesObjectives" : "Strengthen data governance practices; Contribute to risk remediation program", "qualificationsBasic" : "Experience delivering risk, compliance, audit remediation, data governance, or regulatory change initiatives within financial services, Stakeholder management and communication skills, Ability to understand business processes, Experience performing data analysis, Process design, process engineering, or operational improvement experience", "qualificationsPreferred" : "Experience with data masking, Experience with data protection, Experience with privacy controls, Experience with information security programs, Knowledge of banking, Knowledge of payments, Knowledge of enterprise technology environments, Familiarity with audit remediation programs, Familiarity with regulatory examinations, Familiarity with control testing frameworks, Experience designing governance reporting, Experience designing compliance dashboards, Experience designing executive-level status reporting, Understanding of risk management frameworks, Understanding of operational risk practices", "rawDescription" : "Drive Enterprise Risk Remediation Through Data Governance Excellence The Role Capco is seeking a Business Analyst, Data Masking and Compliance to support a critical enterprise audit remediation initiative within a leading financial institution. This newly created role will focus on assessing application compliance against enterprise data masking standards, partnering with stakeholders to drive adoption, and establishing sustainable evidence collection and reporting processes. You will play a key role in bridging business and technology teams, helping application owners understand compliance requirements while ensuring regulatory and audit expectations are met. This is an opportunity to influence enterprise-wide controls, strengthen data governance practices, and contribute to a high-profile risk remediation program. What You’ll Do Assess and prioritize applications requiring review against enterprise data masking standards, identifying compliance gaps and remediation requirements. Partner with application owners and business stakeholders to understand application processes, data flows, and masking requirements. Design and implement evidence collection and validation processes that demonstrate compliance through objective testing rather than attestation alone. Facilitate stakeholder discussions to align business requirements with enterprise standards while supporting adoption of required controls. Create compliance reporting, status tracking, and governance metrics that integrate with broader audit remediation KRIs and KPIs. What We’re Looking For Experience delivering risk, compliance, audit remediation, data governance, or regulatory change initiatives within financial services. Strong stakeholder management and communication skills with the ability to build trust, influence outcomes, and navigate competing priorities. Ability to understand business processes and translate enterprise standards into practical application-level requirements. Experience performing data analysis and interpreting data flows, controls, and compliance requirements. Process design, process engineering, or operational improvement experience with a focus on scalable control frameworks. Bonus Points For Experience with data masking, data protection, privacy controls, or information security programs. Knowledge of banking, payments, and enterprise technology environments. Familiarity with audit remediation programs, regulatory examinations, or control testing frameworks. Experience designing governance reporting, compliance dashboards, and executive-level status reporting. Understanding of risk management frameworks and operational risk practices within large financial institutions. Why Join Capco Work on high-impact regulatory and risk transformation initiatives for leading financial institutions. Partner with senior stakeholders across business, technology, risk, and compliance functions. Join a collaborative, entrepreneurial consulting culture that values innovation and practical problem-solving. Access continuous learning, professional development, and industry-leading expertise. Help shape the future of data governance, compliance, and risk management within the financial services industry. Benefits Comprehensive Benefits Coverage – 100% company-paid health, life, and disability insurance effective from Day 1 of employment. Retirement Savings Program – RRSP with the option of receiving a matching employer contribution. Virtual Health Care and Employee & Family Assistance Program available to employees and their dependents. Enhanced parental leave benefits from Day 1 of employment, plus a company-sponsored new parent gift. Wellness reimbursement and a dedicated Business Coach from Day 1 to support your career growth and development. Why This Role Is Open We are currently hiring for this role due to an existing or newly created vacancy within our organization. This position is open as part of our ongoing business needs, and we are actively reviewing applications to fill this role with a qualified candidate who can make an immediate impact. Inclusion at Capco We’re committed to making our recruitment process accessible and straightforward for everyone. If you need any adjustments at any stage, just let us know – we’ll be happy to help. We value each person’s unique perspective and contribution. At Capco, we believe that being yourself is your greatest strength. Our #BeYourselfAtWork culture encourages individuality and collaboration – a mindset that shapes how we work with clients and each other every day. Use of Artificial Intelligence in Talent Acquisition At Capco, we use artificial intelligence (AI) tools to support and enhance several parts of talent acquisition. This includes using AI-enabled features within LinkedIn to help source potential candidates, speeding up routine recruitment communications such as emails and creating compelling and brand-aligned job postings that accurately reflect role requirements, and AI-scheduling applications to improve the efficiency of interview coordination. AI is used as a support tool only. All hiring decisions are made by talent acquisition and hiring teams. Pay Transparency The salary range for this position is listed below. Additionally, this position may also be eligible to receive an annual discretionary/variable bonus payment. Capco is committed to providing fair and equitable compensation to our people. Our compensation policies and salary ranges are designed to allow our people to progress through the salary range as they demonstrate strong performance and develop in their role over time. The base pay offered to selected candidates will be within the salary range and the placement will vary based upon a variety of factors, including, but not limited to job-related knowledge, skills, experience and internal equity. Canada Pay Transparency $118,000—$152,000 CAD", "summaryDescription" : "Business Analyst, Data Masking and Compliance at Capco. Skills: Data masking, Compliance, Risk remediation, Data governance. Assess applications against data masking standards. Identify compliance gaps", "postedDate" : "2026-06-16T01:20:47.212", "createdAt" : "2026-06-16T01:20:47.212", "lastUpdated" : "2026-06-16T12:32:44.174", "ingestTimestamp" : "2026-06-16T01:20:47.212", "mongoId" : "6a3087a4f292fd229c08b1f8", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ "Data masking standards", "Evidence collection", "Compliance reporting", "Governance metrics", "Data masking", "Compliance", "Risk remediation", "Data governance", "Stakeholder management", "Data analysis", "Process design", "Process engineering", "Operational improvement", "Audit remediation", "Banking", "Payments", "Enterprise technology", "Risk management", "Operational risk" ], "skillCount" : 19, "jobCategory" : "finance", "jobSubcategory" : "accounting", "seniorityLevel" : "Mid", "dataQualityScore" : 0.8888889, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Financial Services", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2ca51974d8ee00a09b4ac2", "title" : "Director, Data Management and Systems", "company" : "Apogee Therapeutics", "industry" : "Biotech", "salary" : { "min" : 215000.0, "max" : 245000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Remote", "locations" : [ "Remote" ], "certifications" : [ "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified" ], "timestamp" : "2026-06-16T00:34:50.028", "fingerprint" : "a67a650203974e35a7812b79bd50b8cc4f96c4b227cf574f7ee5ceabd7897932", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/apogeetherapeutics/jobs/5161364007", "externalId" : "5161364007", "industryFunction" : { }, "structuredLocations" : [ { "country" : "Bulgaria", "continent" : "eu", "workMode" : "remote" } ], "locationText" : "Bulgaria", "employmentType" : "FULL_TIME", "experienceMinYears" : 12, "experienceLevel" : "Director", "technicalSkills" : "SQL, Python, R, Scala, Spark, Dbt, Snowflake, BigQuery, Redshift, Databricks, Fivetran, Airflow, Dbt Cloud, Delta Lake, AWS, GCP, Azure, SageMaker, Vertex AI, ML Studio, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow", "professionalSkills" : [ "Data management", "Systems management", "Data engineering", "Machine learning", "Business intelligence", "Data analytics", "Quantitative analysis", "Statistical modeling" ], "hardSkillsList" : [ "Data warehousing", "ETL processes", "Data modeling", "Database administration", "Cloud computing", "Statistical analysis", "Machine learning algorithms", "Data visualization", "A/B testing", "Causal inference" ], "hardSkills" : [ { "name" : "Data warehousing", "level" : "intermediate" }, { "name" : "ETL processes", "level" : "intermediate" }, { "name" : "Data modeling", "level" : "intermediate" }, { "name" : "Database administration", "level" : "intermediate" }, { "name" : "Cloud computing", "level" : "intermediate" }, { "name" : "Statistical analysis", "level" : "intermediate" }, { "name" : "Machine learning algorithms", "level" : "intermediate" }, { "name" : "Data visualization", "level" : "intermediate" }, { "name" : "A/B testing", "level" : "intermediate" }, { "name" : "Causal inference", "level" : "intermediate" } ], "majorSkills" : "Data management, Systems management, Machine learning, Business intelligence", "majorSkillsList" : [ "Data management", "Systems management", "Machine learning", "Business intelligence" ], "coreResponsibilities" : "Oversee data management systems, Ensure data integrity, Develop and implement data strategies, Manage data governance policies, Lead data engineering initiatives, Build and maintain data pipelines, Optimize data storage and retrieval, Implement data quality controls, Drive analytics and BI initiatives, Develop predictive models, Collaborate with stakeholders", "teamCollaboration" : "Cross-functional teams; Business stakeholders", "domainKnowledge" : "Genomics; Drug discovery; Clinical trials", "domainList" : [ "genomics", "drug-discovery", "clinical-trials" ], "domainSpecificKnowledge" : [ "Genomics", "Drug discovery", "Clinical trials" ], "toolProficiency" : [ "Tableau", "Power BI", "Looker" ], "communicationSkills" : "Stakeholder communication", "documentationSkills" : "Technical documentation", "problemSolvingSkills" : "Analytical skills", "qualificationsBasic" : "5+ years experience, SQL proficiency, Bachelor's degree", "qualificationsPreferred" : "PhD preferred, GCP Professional Data Engineer certification, AWS Data Analytics certification, Databricks Certified certification, Dbt Certified certification, Experience with scikit-learn, Experience with TensorFlow, Experience with PyTorch, Experience with XGBoost, Experience with LightGBM, Experience with Hugging Face, Experience with MLflow", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "About Apogee Therapeutics Founded in 2022, Apogee Therapeutics, Inc. (Ticker: APGE) is a well-funded, Nasdaq listed company that offers the opportunity to work in a fast-paced, highly dynamic environment. At Apogee, you can actively contribute to shaping the company culture, take on various roles and responsibilities, and grow professionally. Apogee Therapeutics is a clinical-stage biotechnology company advancing novel biologics with potential for differentiated efficacy and dosing in the largest I ensure accountability and high-quality deliverables. Lead vendor selection and contract input for DM-related services. People Leadership advanced degree preferred. 12+ years of experience in clinical data management within biotech, pharma, or CRO environments. Experience in both operational DM and systems/technology implementation. Demonstrated leadership of DM activities across multiple clinical trials and programs. Technical Expertise Deep knowledge of EDC systems (e.g., Medidata Rave). Strong understanding of CDISC standards (SDTM, CDASH) and data lifecycle. Experience with data integrations, external data (labs, imaging, biomarkers), and decentralized trial technologies. Familiarity with data visualization and analytics tools is a plus. Leadership & Competencies Proven ability to lead cross-functional teams and influence at the program level. Strong strategic thinking with hands-on execution capability. Excellent communication and stakeholder management skills. Experience in fast-paced, growing organizations preferred. Ability to bridge systems/technology with clinical execution. Strong ownership mindset over data quality and delivery timelines. Proactive, solutions-oriented approach to complex data challenges. Effective leadership in ambiguity and evolving clinical landscapes. The anticipated salary range for candidates for this role will be $215,000 - $245,000/year. The final salary offered will depend on several factors, which may include, but is not limited to relevant years of experience, educational background, and geography. What We Offer A great culture, grounded in our C.O.R. E. values: Caring, Original, Resilient and Egoless Opportunity to work in a fast-paced, highly dynamic environment where you help shape the culture and company, wear multiple hats, and learn quickly Market competitive compensation and benefits package, including base salary, performance bonus, equity grant opportunities, health, welfare & retirement benefits We provide competitive time off, including three weeks PTO, two one-week company-wide shutdowns a year and dedicated paid sick leave Commitment to growing you professionally and providing access to resources to further your development Apogee offers regular all team, in-person meetings to build relationships and problem solve E-Verify Participation: As part of the I9 verification of authorization to work in the US, Apogee participates in E-Verify. To learn more about E-Verify please review this poster. Apogee Therapeutics is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. To review our privacy policy, click here It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.", "summaryDescription" : "Director, Data Management and Systems at Apogee Therapeutics. Skills: Data management, Systems management, Machine learning, Business intelligence. Oversee data management systems. 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We run high-impact data acquisition programs, such as our web crawler and our data partnerships, and work closely with research to build the training datasets for our models. Our work advances the intelligence of our models and teaches them new skills that hundreds of millions of people benefit from every day. ABOUT THE ROLE We are hiring a Program Manager to join our team. In this role, you will lead programs to acquire training data to advance our research roadmap. You will work with researchers to define requirements, design and manage acquisition workflows, and establish processes to execute them at scale. This role requires a blend of strategic thinking and hands-on execution. The ideal candidate can navigate ambiguity, break down complex problems, manage cross-functional stakeholders, and drive alignment across technical and business teams. This role may require living close to some physical operations across the US and some hybrid travel to San Francisco. IN THIS ROLE, YOU WILL: - Work closely with research to understand data needs and define acquisition priorities and timeline that are aligned with our research roadmap. - Translate research objectives into clear technical requirements and operational plans, ensuring data workflows, timelines, and quality standards are executed to the highest quality standards. - Lead vendor and partner engagements for data sourcing – including evaluating suppliers, negotiating agreements, and managing delivery. - Establish and maintain metrics for data quality, throughput, efficiency, and overall program performance, ensuring visibility to leadership and cross-functional partners. - Identify gaps in our data ecosystem and proactively drive initiatives to strengthen our data acquisition and creation capabilities over time. YOU MIGHT THRIVE IN THIS ROLE IF YOU: - Have 8+ years of experience in operations, strategy, venture capital, private equity, or consulting, with at least 5 years operating within a company. We will also consider high-trajectory candidates with fewer years of experience but at top companies with a clear track record of excellence. - Have experience taking end-to-end ownership of large, ambiguous problems, and breaking them down into clear, actionable plans. - Have direct experience engaging with executives and senior leaders to influence and drive strategic decisions. - Excel under pressure, bringing a high motor and exceptional adaptability and flexibility in a fast-paced, dynamic environment. - Are highly analytical - sophisticated in your understanding and approach to analyses; ability to ask and answer the most important questions, and present results clearly to leaders to influence decision making. - Are comfortable operating at all altitudes – discussing strategy and vision with executives, and troubleshooting operations with individual contributors and external partners. - Have excellent communication and cross-functional collaboration skills. - Are passionate about technology and artificial intelligence, and interested in its impact on business and society. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form https://form.asana.com/?d=57018692298241&k=5MqR40fZd7jlxVUh5J-UeA. No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link https://form.asana.com/?k=bQ7w9h3iexRlicUdWRiwvg&d=57018692298241. OpenAI Global Applicant Privacy Policy https://cdn.openai.com/policies/global-employee-and-contractor-privacy-policy.pdf At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. 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IN THIS ROLE, YOU WILL: - Work closely with research to understand data needs and define acquisition priorities and timeline that are aligned with our research roadmap. - Translate research objectives into clear technical requirements and operational plans, ensuring data workflows, timelines, and quality standards are executed to the highest quality standards. - Lead vendor and partner engagements for data sourcing – including evaluating suppliers, negotiating agreements, and managing delivery. - Establish and maintain metrics for data quality, throughput, efficiency, and overall program performance, ensuring visibility to leadership and cross-functional partners. - Identify gaps in our data ecosystem and proactively drive initiatives to strengthen our data acquisition and creation capabilities over time. YOU MIGHT THRIVE IN THIS ROLE IF YOU: - Have 8+ years of experience in operations, strategy, venture capital, private equity, or consulting, with at least 5 years operating within a company. 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About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form https://form.asana.com/?d=57018692298241&k=5MqR40fZd7jlxVUh5J-UeA. No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link https://form.asana.com/?k=bQ7w9h3iexRlicUdWRiwvg&d=57018692298241. OpenAI Global Applicant Privacy Policy https://cdn.openai.com/policies/global-employee-and-contractor-privacy-policy.pdf At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. 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We’re a product-led, fast-moving team at the intersection of AI, fintech, and modern infrastructure. THE ROLE We’re looking for a Senior Data & Platform Engineer to build the data and core platform and infrastructure layer that powers our AI systems. This is not just about pipelines — it’s about creating the systems, tooling, and abstractions that enable engineers and AI workflows to move fast, safely, and reliably. WHAT YOU’LL DO - Design and implement core backend systems and integrations that power the product. - Design and build our data platform (orchestration, pipelines, developer workflows) - Create scalable systems for data ingestion, transformation, and access - Design data models and APIs that won’t collapse under growth. - Make sane decisions about schemas, indexes, migrations, and performance. - Own infrastructure for data + AI workloads (containers, orchestration, cloud services) - Enable self-serve data workflows for engineering and product teams - Improve observability, reliability, and performance across the data stack - Support AI/ML systems (embeddings, vector data, model pipelines) - Build tooling for document processing, metadata, and normalization WHAT WE’RE LOOKING FOR - 7+ years in data engineering, platform engineering, or backend infrastructure - A track record of shipping and owning production systems. - Strong systems thinking (not just pipelines — platform mindset) - Backend system design and API design - Data modeling and relational databases - Performance, reliability, and failure modes - Proficiency in Golang, SQL, Terraform, AWS - Comfort in a fast-moving startup environment BONUS - LLMs / RAG, vector search, fintech or regulated systems - Have startup or early-stage experience. WHY JOIN - Build the foundation layer of an AI-native product - High ownership + direct impact - Work where data, platform, and AI converge THE FIT You’re someone who doesn’t just move data — you build the systems that make data usable at scale.", "summaryDescription" : "Senior Data and Platform Engineer at Avantos. Skills: Data platform, AI systems, Infrastructure. Design backend systems. Implement backend systems", "createdAt" : "2026-06-14T20:21:52.028", "lastUpdated" : "2026-06-16T01:43:36.688", "ingestTimestamp" : "2026-06-14T20:21:52.028", "mongoId" : "6a2cb0de74d8ee00a09db551", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 165000, "salaryAnnualMax" : 225000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Data engineering", "Platform engineering", "Backend infrastructure", "Data platform", "AI systems", "Infrastructure", "Backend system design", "API design", "Data modeling", "System design", "Fintech", "Regulated systems", "Terraform", "AWS", "Docker", "Kubernetes" ], "skillCount" : 16, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Senior", "dataQualityScore" : 0.8888889, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.95 }, { "id" : "6a16291c58b93c861e95a08c", "title" : "Utility Data and Modeling Analyst", "company" : "HDR", "salary" : { "min" : 85000.0, "max" : 115000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline data adjusted for mid-seniority, Saint Louis Park city tier, and the engineering/consulting industry." }, "location" : "Multiple Locations", "locations" : [ "Multiple Locations" ], "timestamp" : "2026-06-16T02:46:45.498", "fingerprint" : "750234fde7fa9a6099369120843b7d86c965903252b6816af102bf9bdbb7676d", "source" : "taleo", "language" : "en", "applyUrl" : "https://hdr.taleo.net/careersection/ex/jobdetail.ftl?job=779912", "externalId" : "779912", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Saint Louis Park", "state" : "Minnesota", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "44.9475726,-93.3569023" } ], "locationText" : "Saint Louis Park, Minnesota, United States", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "technicalSkills" : "SQL, Power Query, Pandas, Python, R, Plotly, Seaborn, Matplotlib", "professionalSkills" : [ "Data engineering", "Business intelligence", "Data science", "Organizational skills" ], "hardSkillsList" : [ "Data modeling" ], "hardSkills" : [ { "name" : "Data modeling", "level" : "intermediate" } ], "majorSkills" : "Data analysis, Data modeling", "majorSkillsList" : [ "Data analysis", "Data modeling" ], "coreResponsibilities" : "Handle confidential information, Prioritize and handle multiple tasks, Manage various managers", "teamCollaboration" : "Employee-owned culture", "domainKnowledge" : "Utility data", "domainList" : [ "utility-data" ], "domainSpecificKnowledge" : [ "Utility data" ], "toolProficiency" : [ "MS Office", "Power BI", "Tableau" ], "communicationSkills" : "Grammar; Punctuation; Proofreading; Spelling; Telephone skills", "qualificationsBasic" : "Degree in closely related field or education/experience combination, Proficiency with MS Office, Proficiency with data engineering tools and languages, Proficiency with business intelligence tools, Proficiency with data science languages, Ability to handle confidential information, Excellent writing and people skills, Math and organizational skills, Flexibility and ability to prioritize, Handle multiple tasks and various managers, Excellent verbal and written communication skills, Commitment to being an active participant of employee-owned culture", "qualificationsPreferred" : "PhD preferred, Specific ML framework experience, Cloud platform certs", "remoteFriendly" : false, "workSiteFlexibility" : "Flexible", "rawDescription" : "Required Qualifications A degree in a closely related field or combination of education and relevant experience Self-motivated, detail-oriented professional, ability to multitask a must Proficiency with MS Office including Word and Outlook Proficiency with data engineering tools and languages such as SQL, Power Query, and Pandas Proficiency with business intelligence tools such as Power BI, Tableau, Plotly, Seaborn, and Matplotlib Proficiency with data science languages such as Python and R Ability to handle confidential information Excellent writing and people skills Strong math and organizational skills Flexibility and ability to prioritize and handle multiple tasks and various managers in a fast-paced environment Excellent verbal and written communication skills including grammar, punctuation, proofreading, spelling and telephone skills An attitude and commitment to being an active participant of our employee-owned culture is a must What We Believe HDR is our company. Together, we build on each other's life experiences and perspectives to make great things possible every day. This shapes our collaborative culture, encourages organizational trust and connects us closer to the clients and communities we serve. Our Commitment As employee owners, we all have a role in creating an inclusive environment where each of us is welcomed, valued, respected and empowered to bring our authentic selves to work every day. Our eight Employee Network Groups (Asian Pacific, Black, Hispanic/Latino(a), LGBTQ+, People with Disabilities, Veterans, Women, Young Professionals) help create a sense of belonging and foster a supportive environment where everyone is empowered to engage and contribute. Each group has an executive sponsor and is open to all employees. United States-Minnesota-Saint Louis Park", "summaryDescription" : "Utility Data and Modeling Analyst at HDR. Skills: Data analysis, Data modeling. Handle confidential information. Prioritize and handle multiple tasks", "createdAt" : "2026-06-14T21:31:19.547", "lastUpdated" : "2026-06-16T02:46:45.498", "ingestTimestamp" : "2026-06-14T21:31:19.547", "mongoId" : "6a16291c58b93c861e95a08c", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 85000, "salaryAnnualMax" : 115000, "salaryBand" : "75k-100k", "hasSalary" : true, "allSkills" : [ "Data modeling", "Data analysis", "Data engineering", "Business intelligence", "Data science", "Organizational skills", "Utility data", "MS Office", "Power BI", "Tableau" ], "skillCount" : 10, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Mid", "dataQualityScore" : 0.7777778, "hasLocation" : true, "hasGeo" : true, "llmIndustryConfidence" : 0.92 }, { "id" : "69cf3f062beec4dd3d9340ff", "title" : "Data and Analytics Architect", "company" : "ADCI HYD", "industry" : "Operations, IT, Support Engineering, Solution Architect, Cloud Computing", "salary" : { "min" : 2500000.0, "max" : 4000000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Senior Data and Analytics Architect in Hyderabad, India, adjusted for the FinTech industry and company size." }, "location" : "Hyderabad, Telangana, IND", "locations" : [ "Hyderabad, Telangana, IND" ], "timestamp" : "2026-06-15T07:27:32.772", "fingerprint" : "5ad498afe6ceb25c77afff66f9b663db573be509c4597dad8763d7801ca5c8cb", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/10382143/apply", "externalId" : "fe65d693-5feb-466a-8c26-5393f1ddf5b6", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Hyderabad", "state" : "Telangana", "country" : "India", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "17.3605890,78.4740613" } ], "locationText" : "Hyderabad, Telangana, India", "employmentType" : "FULL_TIME", "experienceMinYears" : 6, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "AWS, Redshift, S3, AWS Glue, Amazon Athena, Amazon QuickSight, AWS Lambda, EMR, Kinesis, FireHose, IAM, SAP", "professionalSkills" : [ "Data engineering", "Analytics architecture", "Data platform design", "Data ingestion", "Data transformation", "Data storage", "Semantic modeling", "Reporting", "Analytics patterns", "Data pipelines", "Data processing", "Reporting architectures", "Data quality", "Data governance", "Data security", "Operational controls", "Business requirements", "Architecture standards", "Data flow diagrams", "Support procedures", "Performance issues", "Data quality concerns", "Corrective actions", "Implementation initiatives", "Migration initiatives", "Modernization initiatives", "Enhancement initiatives", "Platform integration" ], "hardSkillsList" : [ "Data engineering", "Database engineering", "Business intelligence", "Business analytics", "Data warehousing", "Enterprise data platform", "Data pipelines", "Analytics solutions", "Data processing", 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"Data integration", "level" : "intermediate" } ], "majorSkills" : "Data architecture, AWS data services, Data platform design", "majorSkillsList" : [ "Data architecture", "AWS data services", "Data platform design" ], "coreResponsibilities" : "Lead design of data solutions, Lead implementation of data solutions, Lead support of data solutions, Architect data platforms using AWS, Define data ingestion patterns, Implement data ingestion patterns, Define data transformation patterns, Implement data transformation patterns, Define data storage patterns, Implement data storage patterns, Define semantic modeling patterns, Implement semantic modeling patterns, Define reporting patterns, Implement reporting patterns, Define analytics patterns, Implement analytics patterns, Design data pipelines, Optimize data pipelines, Design batch data processing, Optimize batch data processing, Design near real-time processing, Optimize near real-time processing, Design reporting architectures, Optimize reporting architectures, Ensure data quality, Ensure data governance, Ensure data security, Ensure operational controls, Work with business teams, Work with finance teams, Work with IT teams, Work with application teams, Design reliable data solutions, Design scalable data solutions, Develop architecture standards, Maintain architecture standards, Develop design documents, Maintain design documents, Develop data flow diagrams, Maintain data flow diagrams, Develop support procedures, Maintain support procedures, Monitor data pipelines, Monitor analytics platforms, Monitor reporting solutions, Drive corrective actions", "teamCollaboration" : "Business teams; Finance teams; IT teams; Application teams", "domainKnowledge" : "FinTech; SAP data; Finance reporting; Supply chain reporting; Enterprise operational reporting", "domainList" : [ "fintech", "sap-data", "finance-reporting", "supply-chain-reporting", "enterprise-operational-reporting" ], "domainSpecificKnowledge" : [ "FinTech", "SAP 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Knowledge of supply chain reporting domains, Knowledge of enterprise operational reporting domains, Experience leading data modernization initiatives, Experience leading cloud transformation initiatives", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "We are seeking an experienced Data and Analytics Architect to join our team. The ideal candidate will be responsible for leading the design, implementation, and support of scalable data and analytics solutions on AWS, enabling trusted reporting, enterprise insights, and seamless integration across enterprise platforms. The primary focus of this role is AWS-based data engineering, analytics architecture, and modern data platform design, with SAP knowledge considered a strong advantage. Key job responsibilities * Lead the design, implementation, and support of enterprise data and analytics solutions on AWS. * Architect scalable data platforms using AWS services such as Amazon Redshift, Amazon S3, AWS Glue, Amazon Athena, Amazon QuickSuite, AWS Lambda, and related AWS data services. * Define and implement data ingestion, transformation, storage, semantic modeling, reporting, and analytics patterns across structured and semi-structured data sources. * Design and optimize enterprise data pipelines, batch and near real-time data processing, and reporting architectures. * Ensure data quality, governance, security, and operational controls are built into the platform architecture. * Work closely with business, finance, IT, and application teams to design reliable and scalable data solutions aligned with business requirements. * Develop and maintain architecture standards, design documents, data flow diagrams, and support procedures. * Monitor data pipelines, analytics platforms, and reporting solutions for failures, performance issues, and data quality concerns, and drive corrective actions. * Lead implementation, migration, modernization, and enhancement initiatives across data and analytics platforms. * Support integration with enterprise platforms, including SAP and non-SAP systems where required. Basic Qualifications: - Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions - 6+ years of data engineering, database engineering, business intelligence or business analytics experience - 8+ years of relevant experience in data engineering, analytics, data warehousing, or enterprise data platform implementation and support. - Experience designing scalable data pipelines and cloud-based analytics solutions across complex enterprise environments. - Excellent analytical, problem-solving, and stakeholder management skills, with the ability to work independently and as part of a team. Preferred Qualifications: - Knowledge of SAP data and analytics platforms such as SAP S/4HANA, BW, Datasphere, or SAC is good to have. - Experience with real-time or event-driven data processing patterns. - Experience with data lake, data warehouse, and hybrid analytics architecture patterns. - Experience with enterprise reporting, KPI frameworks, and dashboard design. - Knowledge of finance, supply chain, or enterprise operational reporting domains. - Experience leading data modernization or cloud transformation initiatives. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.", "summaryDescription" : "Data and Analytics Architect at ADCI HYD. Skills: Data architecture, AWS data services, Data platform design. Lead design of data solutions. Lead implementation of data solutions", "postedDate" : "2026-06-13T14:22:44.066", "createdAt" : "2026-06-13T14:22:44.066", "lastUpdated" : "2026-06-15T07:27:32.772", "ingestTimestamp" : "2026-06-13T14:22:44.066", "mongoId" : "69cf3f062beec4dd3d9340ff", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/10382143/apply", "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Data engineering", "Database engineering", "Business intelligence", "Business analytics", "Data warehousing", "Enterprise data platform", "Data pipelines", "Analytics solutions", "Data processing", "Reporting architectures", "Data quality", "Data governance", "Data security", "Operational controls", "Data integration", "Data architecture", "AWS data services", "Data platform design", "Analytics architecture", "Data ingestion", "Data transformation", "Data storage", "Semantic modeling", "Reporting", "Analytics patterns", "Business requirements", "Architecture standards", "Data flow diagrams", "Support procedures", "Performance issues", "Data quality concerns", "Corrective actions", "Implementation initiatives", "Migration initiatives", "Modernization initiatives", "Enhancement initiatives", "Platform integration", "FinTech", "SAP data", "Finance reporting", "Supply chain reporting", "Enterprise operational reporting" ], "skillCount" : 42, "jobCategory" : "operations", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true }, { "id" : "6a210e4274d8ee00a0af6952", "title" : "AI and Data Engineer, Google Cloud", "company" : "Google", "industry" : "Technology", "salary" : { "min" : 3500000.0, "max" : 5500000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market data for AI and Data Engineer roles in Bengaluru, India, adjusted for mid-seniority at a large technology company." }, "location" : "[Bengaluru, Karnataka, India, [3, Old Madras Rd, Sadanandanagar, 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: "https://jobs.lever.co/jobgether/2b7d6fbe-231c-4004-828c-8606bceba0b0/apply", "externalId" : "2b7d6fbe-231c-4004-828c-8606bceba0b0", "industryFunction" : { }, "structuredLocations" : [ { "country" : "Bulgaria", "continent" : "eu", "workMode" : "remote" } ], "locationText" : "Bulgaria", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Oracle Analytics Cloud, ETL, Power BI", "professionalSkills" : [ "Data modeling", "Data governance", "Self-service BI", "User access management", "Data quality processes", "ETL optimization", "System troubleshooting", "Project planning", "Stakeholder management" ], "hardSkillsList" : [ "Data ingestion", "Data transformation", "Reporting logic", "Data cleansing", "Reporting needs" ], "softSkillsList" : [ "Problem-solving" ], "hardSkills" : [ { "name" : "Data ingestion", "level" : "intermediate" }, { "name" : "Data transformation", "level" : "intermediate" }, { "name" : "Reporting logic", "level" : "intermediate" }, { "name" : "Data cleansing", "level" : "intermediate" }, { "name" : "Reporting needs", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Problem-solving" } ], "majorSkills" : "Data architecture, Data analytics, Business intelligence", "majorSkillsList" : [ "Data architecture", "Data analytics", "Business intelligence" ], "coreResponsibilities" : "Develop and maintain stakeholder relationships, Ensure data and analytics solutions align with business, Enhance and maintain stability of OAC environments, Enhance and maintain performance of OAC environments, Enhance and maintain scalability of OAC environments, Design data ingestion strategies, Support data ingestion strategies, Establish data governance standards, Maintain data governance standards, Document data sources, Document transformations, Document reporting logic, Promote self-service BI adoption, Promote visualization best practices, Manage user access, Manage security, Manage provisioning for analytics platforms, Support data quality processes, Validate data, Cleanse data, Optimize ETL, Collaborate with business users, Collaborate with IT teams, Troubleshoot system issues, Deliver enhancements, Support reporting needs, Participate in SDLC processes, Participate in project planning, Participate in Agile ceremonies, Communicate status updates, Communicate risks, Contribute to dashboard development, Contribute to report creation, Contribute to migration efforts, Lift and shift OAC content into Power BI", "teamCollaboration" : "Cross-functional collaboration efforts; Business users; IT teams", "projectManagementSkills" : [ "Agile ceremonies", "Project planning", "SDLC processes" ], "domainKnowledge" : "Data lake architectures; Modern data warehouse architectures; Enterprise BI architectures", "domainList" : [ "data-lake-architectures", "modern-data-warehouse-architectures", "enterprise-bi-architectures" ], "domainSpecificKnowledge" : [ "Data lake architectures", "Modern data warehouse architectures", "Enterprise BI architectures" ], "toolProficiency" : [ "Oracle Analytics Cloud", "Power BI" ], "communicationSkills" : "Presentation; Stakeholder management; Explain analytical insights", "documentationSkills" : "Documentation of data sources; Documentation of transformations; Documentation of reporting logic", "problemSolvingSkills" : "Problem-solving abilities", "specialRequirements" : "Willingness to travel periodically", "qualificationsBasic" : "Bachelor's degree in Computer Science, Information Systems, Business Administration, or related field, 5+ years of experience in BI, data analytics, or data architecture roles, Experience with relational databases, Data modeling concepts, ETL processes, Flat file data integration, Deep understanding of data analytics platforms, Reporting frameworks, Enterprise BI architectures, Ability to translate business requirements into technical data solutions, Explain analytical insights in simple terms, Experience working with stakeholders to define priorities, Gather requirements, Deliver data-driven solutions, Knowledge of Agile/Scrum methodologies, Basic project management principles, Communication skills, Presentation skills, Stakeholder management skills", "qualificationsPreferred" : "Hands-on experience with Microsoft Power BI or similar data visualization tools, Familiarity with data lake concepts, Emerging modern data warehouse architectures", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "## Accountabilities Develop and maintain strong stakeholder relationships to ensure data and analytics solutions align with evolving business requirements and priorities. Enhance and maintain stability, performance, and scalability of existing Oracle Analytics Cloud (OAC) environments. Design and support data ingestion strategies for modern data lake architectures using ETL tools, flat file processing, and integration frameworks. Establish and maintain data governance standards, including documentation of data sources, transformations, and reporting logic. Promote self-service BI adoption and visualization best practices across the organization using OAC and Power BI platforms. Manage user access, security, and provisioning for analytics platforms, ensuring appropriate governance and compliance. Support data quality processes including validation, cleansing, and ETL optimization to ensure reliable reporting outputs. Collaborate with business users and IT teams to troubleshoot system issues, deliver enhancements, and support reporting needs. Participate in SDLC processes, project planning, and Agile ceremonies while ensuring timely communication of status updates and risks. Contribute to dashboard development, report creation, and migration efforts including the “lift and shift” of legacy OAC content into Power BI. Requirements: Bachelor’s degree in Computer Science, Information Systems, Business Administration, or related field. 5+ years of experience in BI, data analytics, or data architecture roles covering design, development, implementation, and support of enterprise analytics solutions. Strong experience with relational databases, data modeling concepts, ETL processes, and flat file data integration. Hands-on experience with Microsoft Power BI or similar data visualization tools strongly preferred. Deep understanding of data analytics platforms, reporting frameworks, and enterprise BI architectures. Strong ability to translate business requirements into technical data solutions and explain analytical insights in simple terms. Experience working with stakeholders to define priorities, gather requirements, and deliver data-driven solutions. Familiarity with data lake concepts and emerging modern data warehouse architectures. Knowledge of Agile/Scrum methodologies and basic project management principles. Strong communication, presentation, and stakeholder management skills across technical and non-technical audiences. Self-starter mindset with strong problem-solving abilities and ability to lead cross-functional collaboration efforts. Willingness to travel periodically as required. Benefits: Competitive base salary with performance-based incentive compensation. Comprehensive health coverage including medical, dental, and vision insurance. Life insurance, disability coverage, and additional voluntary benefit options. Immediate eligibility for 401(k) with employer matching contributions. Generous paid time off including 80 hours (10 days) of company holidays annually. Adoption benefits and family support programs. Inclusive work environment with equal opportunity employment practices. Exposure to modern data architecture transformation and enterprise BI modernization initiatives. ## Additional Information How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1", "summaryDescription" : "Solutions Architect IV- Data and Analytics. Skills: Data architecture, Data analytics, Business intelligence. Develop and maintain stakeholder relationships. Ensure data and analytics solutions align with business", "postedDate" : "2026-06-15T10:16:20.862", "createdAt" : "2026-06-15T10:16:20.862", "lastUpdated" : "2026-06-16T11:33:50.217", "ingestTimestamp" : "2026-06-16T03:20:53.708", "mongoId" : "6a30511af292fd229cefa673", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "75k-100k", "hasSalary" : false, "allSkills" : [ "Data ingestion", "Data transformation", "Reporting logic", "Data cleansing", "Reporting needs", "Problem-solving", "Data architecture", "Data analytics", "Business intelligence", "Data modeling", "Data governance", "Self-service BI", "User access management", "Data quality processes", "ETL optimization", "System troubleshooting", "Project planning", "Stakeholder management", "Agile ceremonies", "SDLC processes", "Data lake architectures", "Modern data warehouse architectures", "Enterprise BI architectures", "Oracle Analytics Cloud", "Power BI" ], "skillCount" : 25, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Senior", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a305119f292fd229cef9c97", "title" : "Lead Product Manager, Data and AI", "industry" : "Product", "salary" : { "min" : 85000.0, "max" : 130000.0, "currency" : "EUR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Lead Product Manager, Data and AI in Bulgaria, adjusted for SaaS industry and remote work." }, "location" : "US", "locations" : [ "US" ], "timestamp" : "2026-06-16T13:00:21.262", "fingerprint" : "82fe4f4fdc8ab1372055aa6158ae911736d6dc6afa73b5b74d4c6341bc3b8381", "source" : "lever", "language" : "en", "applyUrl" : "https://jobs.lever.co/jobgether/f4b9f71e-4327-4077-a695-5a7cf7ad3271/apply", "externalId" : "f4b9f71e-4327-4077-a695-5a7cf7ad3271", "industryFunction" : { }, "structuredLocations" : [ { "country" : "Bulgaria", "continent" : "eu", "workMode" : "remote" } ], "locationText" : "Bulgaria", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "experienceMinYears" : 8, "experienceMaxYears" : 15, "experienceLevel" : "Lead", "technicalSkills" : "Machine learning, Generative AI, Large language models, LLMs, Advanced analytics", "professionalSkills" : [ "Product strategy", "Roadmap development", "Product lifecycle management", "Stakeholder management", "Product requirements", "Data-driven decision making" ], "hardSkillsList" : [ "AI development", "Analytics solutions", "Product performance measurement", "Experimentation frameworks" ], "softSkillsList" : [ "Leadership", "Mentoring" ], "hardSkills" : [ { "name" : "AI development", "level" : "intermediate" }, { "name" : "Analytics solutions", "level" : "intermediate" }, { "name" : "Product performance measurement", "level" : "intermediate" }, { "name" : "Experimentation frameworks", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" } ], "majorSkills" : "Machine learning, Generative AI, Analytics solutions", "majorSkillsList" : [ "Machine learning", "Generative AI", "Analytics solutions" ], "coreResponsibilities" : "Define product vision and roadmap, Execute product vision and roadmap, Align initiatives with business objectives, Lead development of AI solutions, Lead deployment of AI solutions, Manage product lifecycle, Collaborate with cross-functional stakeholders, Integrate intelligent capabilities into products, Establish frameworks for measuring product performance, Establish frameworks for experimentation, Establish frameworks for business impact, Use data-driven insights for decision-making, Use data-driven insights for optimization, Translate business challenges into product requirements, Act as bridge between technical and non-technical stakeholders, Promote responsible AI development, Partner with governance stakeholders, Partner with privacy stakeholders, Partner with compliance stakeholders, Ensure ethical product outcomes, Ensure secure product outcomes, Ensure reliable product outcomes, Mentor team members, Contribute to product management best practices, Foster culture of innovation, Foster culture of collaboration, Foster culture of continuous improvement", "teamCollaboration" : "Cross-functional stakeholders; Product teams; Engineering teams; Design teams; Operations teams; Business teams; Multidisciplinary teams", "projectManagementSkills" : [ "Roadmap development", "Prioritization", "Execution" ], "domainKnowledge" : "Machine learning concepts; Generative AI technologies; Large language models; LLMs; Advanced analytics; AI infrastructure; Data privacy; Data governance; AI security; Ethical AI principles", "domainList" : [ "machine-learning-concepts", "generative-ai-technologies", "large-language-models", "llms", "advanced-analytics", "ai-infrastructure", "data-privacy", "data-governance", "ai-security", "ethical-ai-principles" ], "domainSpecificKnowledge" : [ "Machine learning concepts", "Generative AI technologies", "Large language models", "LLMs", "Advanced analytics", "AI infrastructure", "Data privacy", "Data governance", "AI security", "Ethical AI principles" ], "communicationSkills" : "Explain technical concepts; Explain trade-offs", "continuousLearning" : "Product management best practices", "innovationCreativity" : "Culture of innovation", "problemSolvingSkills" : "Navigate ambiguity; Prioritize competing objectives; Execute complex initiatives", "qualificationsBasic" : "Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related quantitative discipline, 8+ years of product management experience within enterprise SaaS, cloud software, technology, or highly regulated industries, At least 3 years of hands-on experience launching and scaling machine learning, AI, or data-driven products, Deep understanding of machine learning concepts, generative AI technologies, large language models (LLMs), advanced analytics, and the infrastructure required to support AI solutions, Proven ability to develop product strategies, navigate ambiguity, prioritize competing objectives, and successfully execute complex initiatives, Experience working across multidisciplinary teams in fast-paced environments", "qualificationsPreferred" : "Familiarity with regulated industries, Understanding of data privacy, governance, security, and ethical AI principles", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "## Accountabilities Define and execute a multi-year product vision and roadmap for data and AI platforms, aligning initiatives with business objectives, growth strategies, and operational priorities. Lead the development and deployment of advanced AI, machine learning, generative AI, and analytics solutions, managing the full product lifecycle from ideation and experimentation to scalable production delivery. Collaborate closely with cross-functional stakeholders across product, engineering, design, operations, and business teams to integrate intelligent capabilities into core products and workflows. Establish frameworks for measuring product performance, experimentation, and business impact, using data-driven insights to guide decision-making and optimization efforts. Translate complex business challenges into clear product requirements and act as a bridge between technical specialists and non-technical stakeholders. Promote responsible AI development by partnering with governance, privacy, and compliance stakeholders to ensure ethical, secure, and reliable product outcomes. Mentor team members, contribute to product management best practices, and help foster a culture of innovation, collaboration, and continuous improvement. Requirements Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related quantitative discipline. 8+ years of product management experience within enterprise SaaS, cloud software, technology, or highly regulated industries, with a strong track record of delivering large-scale products. At least 3 years of hands-on experience launching and scaling machine learning, AI, or data-driven products. Deep understanding of machine learning concepts, generative AI technologies, large language models (LLMs), advanced analytics, and the infrastructure required to support AI solutions. Proven ability to develop product strategies, navigate ambiguity, prioritize competing objectives, and successfully execute complex initiatives. Strong communication and stakeholder management skills, with the ability to explain technical concepts and trade-offs to executive and non-technical audiences. Experience working across multidisciplinary teams in fast-paced environments and influencing decisions without direct authority. Familiarity with regulated industries and an understanding of data privacy, governance, security, and ethical AI principles is considered a strong advantage. Benefits Annual base salary ranging from $161,000 to $221,500, depending on experience, qualifications, and location. Eligibility for performance-based or discretionary bonus programs. Comprehensive healthcare coverage, including medical, dental, vision, life, and disability insurance options. Flexible spending accounts (FSA) and health savings account (HSA) programs. Access to coaching, therapy, and well-being support services. Equity participation through company stock programs. Generous paid time off, including vacation, sick leave, and company holidays. Paid parental leave. 401(k) retirement plan with company matching contributions. Monthly technology allowance. Additional wellness initiatives, employee events, recognition programs, and community-focused activities. ## Additional Information How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1", "summaryDescription" : "Lead Product Manager, Data and AI. Skills: Machine learning, Generative AI, Analytics solutions. Define product vision and roadmap. Execute product vision and roadmap", "postedDate" : "2026-06-15T09:26:38.520", "createdAt" : "2026-06-15T09:26:38.520", "lastUpdated" : "2026-06-16T13:00:21.262", "ingestTimestamp" : "2026-06-16T03:24:32.331", "mongoId" : "6a305119f292fd229cef9c97", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "75k-100k", "hasSalary" : false, "allSkills" : [ "AI development", "Analytics solutions", "Product performance measurement", "Experimentation frameworks", "Leadership", "Mentoring", "Machine learning", "Generative AI", "Product strategy", "Roadmap development", "Product lifecycle management", "Stakeholder management", "Product requirements", "Data-driven decision making", "Prioritization", "Execution", "Machine learning concepts", "Generative AI technologies", "Large language models", "LLMs", "Advanced analytics", "AI infrastructure", "Data privacy", "Data governance", "AI security", "Ethical AI principles" ], "skillCount" : 26, "jobCategory" : "product", "jobSubcategory" : "product_management", "seniorityLevel" : "Lead", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "SaaS", "llmIndustryConfidence" : 0.98 }, { "id" : "6a306002f292fd229cf84369", "title" : "Sr. Manager, Statistical Programming and Data Operations", "company" : "Kyowa Kirin North America", "industry" : "Pharma", "salary" : { "min" : 145000.0, "max" : 160000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Princeton, New Jersey, United States", "locations" : [ "Princeton", "New Jersey", "United States" ], "timestamp" : "2026-06-16T08:50:44.103", "fingerprint" : "49d9cfec2d36afaf4e7072ec9fd00eb8eee6a4c344e64335be311f83397963b8", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/kyowakirinusa90/jobs/7773426003", "externalId" : "7773426003", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Princeton", "state" : "New Jersey", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "hybrid", "geo" : "40.3496953,-74.6597376" }, { "city" : "San Diego", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "hybrid", "geo" : "32.7174202,-117.1627720" }, { "city" : "San Francisco", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "hybrid", "geo" : "37.7879363,-122.4075201" } ], "locationText" : "Princeton, New Jersey, United States; San Diego, California, United States; San Francisco, California, United States", "employmentType" : "FULL_TIME", "experienceLevel" : "Manager", "technicalSkills" : "SAS, R, Microsoft Office", "professionalSkills" : [ "Vendor oversight", "Project management", "Data standards" ], "hardSkillsList" : [ "Statistical programming", "CDISC compliant submission", "Regulatory documents" ], "hardSkills" : [ { "name" : "Statistical programming", "level" : "intermediate" }, { "name" : "CDISC compliant submission", "level" : "intermediate" }, { "name" : "Regulatory documents", "level" : "intermediate" } ], "majorSkills" : "Statistical programming, CDISC standards, Vendor management", "majorSkillsList" : [ "Statistical programming", "CDISC standards", "Vendor management" ], "coreResponsibilities" : "Develop TLF shells, Develop CDISC deliverables, Develop TLFs, Participate in vendor selection, Oversee vendor processes, Review Requests for Proposal, Track stat/programming activities, Manage project budget, Manage timeline of deliverables, Ensure statistical deliverables meet timelines, Oversee statistical programming tasks, Manage stat/programming TMFs, Act as subject matter expert, Interface with in-house staff, Participate on project team, Manage cost of activities, Manage timeline of activities, Review protocols, Review case report forms, Review statistical analysis plans, Review specifications for raw data, Review clinical study reports, Review study-related documents, Provide statistical programming input, Prepare CDISC data submission package, Prepare SAS programming for regulatory documents, Provide statistical programming for publications, Provide statistical programming for presentations, Provide ad-hoc analyses, Provide post-hoc analyses, Conduct programming QC reviews, Support departmental initiatives, Improve programming activities, Coordinate with Japanese colleagues, Liaise regarding global procedures, Liaise regarding global processes, Liaise regarding global standards", "teamCollaboration" : "Cross-regional staffs; Project team; Japanese colleagues", "projectManagementSkills" : [ "Timeline management", "Budget management" ], "domainKnowledge" : "Clinical trials; Drug development; ICH guidelines; Regulatory guidance; Life sciences industry; Biostatistics; CDISC standards", "domainList" : [ "clinical-trials", "drug-development", "ich-guidelines", "regulatory-guidance", "life-sciences-industry", "biostatistics", "cdisc-standards" ], "domainSpecificKnowledge" : [ "Clinical trials", "Drug development", "ICH guidelines", "Regulatory guidance", "Life sciences industry", "Biostatistics", "CDISC standards" ], "toolProficiency" : [ "SAS", "Microsoft Office" ], "documentationSkills" : "TLF shells; CDISC datasets; Regulatory documents", "specialRequirements" : "FDA inspections", "qualificationsBasic" : "Bachelor's Degree or higher in Computer Science, Statistics, or related discipline, Six or more years of experience with a Master's degree, Eight or more years of experience with a Bachelor's degree, Proven experience in statistical programming for clinical trials, Experience in study oversight of statistical analysis for clinical trials, Demonstrated expertise in CDISC standards, Excellent proficiency in SAS", "qualificationsPreferred" : "Experience in data integration for ISS/ISE, Experience using SAS-LSAF, Advance skill in R", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "Kyowa Kirin is a fast-growing global specialty pharmaceutical company that applies state-of-the-art biotechnologies to discover and deliver novel medicines in four disease areas: bone and mineral; intractable hematologic; hematology oncology; and rare disease. A Japan-based company, our goal is to translate science into smiles by delivering therapies where no adequate treatments currently exist, working from drug discovery to product development and commercialization. In North America, we are headquartered in Princeton, NJ, with offices in California, North Carolina, and Mississauga, Ontario. Summary: Manager, Statistical Programming and Data Operations (SPDO) in Biostatistics is responsible for vendor oversight and management to deliver the high-quality tables, listings, and figures (TLFs), as well as CDISC datasets for clinical trials and integrated statistical analysis intended for regulatory submissions, interfacing with cross-regional staffs in establishing and maintaining global data standards and department procedures. Essential Functions: Vendor Oversight and Management • Responsible for developing TLF shells, CDISC deliverables, and TLFs in collaboration with stat/programming vendors. • Participate in vendor selection/oversight processes: Create and/or review Requests for Proposal (RFP); track the progress of stat/programming activities and the project budget for stat/programming vendor; and manage the timeline of stat/programming deliverables. • Collaborate with stat/programming vendors to ensure all statistical deliverables from the vendor meet timelines with quality. Oversee all aspects of statistical programming tasks performed by the vendor. • Manage the stat/programming related TMFs in collaboration with stat/programming vendors and act as a subject matter expert at FDA inspections. Internal Collaboration • Interface with in-house staff: Participate on project team meetings; and manage the cost and timeline of stat/programming activities in collaboration with each project manager. • Review protocols, case report forms, statistical analysis plans, specifications for raw data, clinical study reports, and the other study-related documents. • Collaborate with biostatistician to provide statistical programming input on project topics and issues. Statistical Programming • Responsible for preparation of CDISC data submission package and SAS programming for regulatory documents (e. g. Response to information requests from HA; Integrated summaries; BIMO; and DSUR). • Provide statistical programming for publications and presentations, ad-hoc and post-hoc analyses of clinical study data. • Conduct programming QC reviews of vendor deliverables in accordance with internal guidelines and work instructions. • Support departmental initiatives related to process building/improvement of programming activities. • Coordinate and liaise with our Japanese colleagues, as needed, regarding global procedures, processes, and standards. Requirements: Education Bachelor’s Degree or higher in Computer Science, Statistics, or closely related discipline. Experience • Proven experience in statistical programming for clinical trials in the life sciences industry: six or more years with a Master’s degree, or eight or more years with a Bachelor’s degree. • Experience in study oversight of statistical analysis for clinical trials in the life science industry • Demonstrated expertise in CDISC standards and CDISC compliant submission requirements. • Experience in data integration for ISS/ISE across multiple studies for regulatory submissions (preferred) • Experience in using SAS-LSAF (i. e. Life Science Analytics Framework), including its repository and programming environment (preferred) Technical Skills • Excellent proficiency in SAS (required); Advance skill in R (preferred). • Highly skilled in Microsoft Office applications (Word, PowerPoint, Excel, Outlook). • Familiarity with ICH guidelines (especially E9) and other regulatory guidance. • Solid understanding of development, regulatory and commercial aspects of drug development. The anticipated salary for this position will be $145,000 to $160,000. The actual salary offered for this role at commencement of employment may vary based on several factors including but not limited to relevant experience, skill set, qualifications, education (including applicable licenses and certifications, job-based knowledge, location, and other business and organizational needs. The listed salary is just one component of the overall compensation package. At Kyowa Kirin North America we provide a comprehensive range of benefits including: 401K with company match Annual Bonus Program (Sales Bonus for Sales Jobs) Generous PTO and Holiday Schedule which includes Summer and Winter Shut-Downs, Sick Days and, Volunteer Days Healthcare Benefits (Medical, Dental, Prescription Drugs and Vision) HSA Kyowa Kirin is not responsible for any fees related to unsolicited resumes. #Hybrid #Princeton", "summaryDescription" : "Sr. Manager, Statistical Programming and Data Operations at Kyowa Kirin North America. Skills: Statistical programming, CDISC standards, Vendor management. Develop TLF shells. Develop CDISC deliverables", "postedDate" : "2026-06-15T23:25:02.678", "createdAt" : "2026-06-15T23:25:02.678", "lastUpdated" : "2026-06-16T08:50:44.103", "ingestTimestamp" : "2026-06-15T23:25:02.678", "mongoId" : "6a306002f292fd229cf84369", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 145000, "salaryAnnualMax" : 160000, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ "Statistical programming", "CDISC compliant submission", "Regulatory documents", "CDISC standards", "Vendor management", "Vendor oversight", "Project management", "Data standards", "Timeline management", "Budget management", "Clinical trials", "Drug development", "ICH guidelines", "Regulatory guidance", "Life sciences industry", "Biostatistics", "SAS", "Microsoft Office" ], "skillCount" : 18, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Manager", "dataQualityScore" : 1.0, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Pharma", "llmIndustryConfidence" : 0.95 }, { "id" : "69ce5e3b9bc74574cb677aec", "title" : "T6_Chief Data and AI Architect", "company" : "MBRDI", "industry" : "Manufacturing", "salary" : { "min" : 6000000.0, "max" : 9000000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for an Executive Chief Data and AI Architect in Bangalore, India, adjusted for industry and company size." }, "location" : "India-Karnataka-Bangalore", "locations" : [ "India-Karnataka-Bangalore", "Brigade Tech Gardens, Katha No. 119, Kundalahalli Village, K.R. Puram Hobli, Ward No. 85, Bangalore" ], "certifications" : [ "Azure Data Engineer", "Azure Architect", "AWS Certified Machine Learning" ], "timestamp" : "2026-06-15T10:23:16.352", "fingerprint" : "370e2b00770dd492a2575292193f9eb76fd8365da30dfb9faa3fab6b2d172cdd", "source" : "taleo", "language" : "en", "applyUrl" : "https://daimler.taleo.net/careersection/ex/jobdetail.ftl?job=877618", "externalId" : "877618", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Bangalore", "state" : "Karnataka", "country" : "India", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "12.9767936,77.5900820" } ], "locationText" : "Bangalore, Karnataka, India", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "experienceMinYears" : 10, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Data Architecture, Data Engineering, AI, ML, Spark, Dbt, Kafka, Databricks, Synapse, Snowflake, APIs, Python, R, Scala, TensorFlow, PyTorch, Azure ML, SageMaker, Delta Lake, AWS, GCP, Azure", "professionalSkills" : [ "Solution design", "Stakeholder management", "Team leadership", "Thought leadership", "Knowledge sharing", "Technical excellence" ], "hardSkillsList" : [ "Data modeling", "Data ingestion", "Data integration", "Metadata management", "Data lineage", "Data quality", "Model lifecycle management", "Model versioning", "Model monitoring", "Risk assessment" ], "hardSkills" : [ { "name" : "Data modeling", "level" : "intermediate" }, { "name" : "Data ingestion", "level" : "intermediate" }, { "name" : "Data integration", "level" : "intermediate" }, { "name" : "Metadata management", "level" : "intermediate" }, { "name" : "Data lineage", "level" : "intermediate" }, { "name" : "Data quality", "level" : "intermediate" }, { "name" : "Model lifecycle management", "level" : "intermediate" }, { "name" : "Model versioning", "level" : "intermediate" }, { "name" : "Model monitoring", "level" : "intermediate" }, { "name" : "Risk assessment", "level" : "intermediate" } ], "majorSkills" : "Data Architecture, AI, ML, Data Engineering", "majorSkillsList" : [ "Data Architecture", "AI", "ML", "Data Engineering" ], "coreResponsibilities" : "Design scalable data architectures, Oversee data ingestion, Oversee data integration, Oversee data transformation, Define metadata best practices, Define data lineage best practices, Define data quality best practices, Lead data model development, Lead data pipeline development, Lead data transformation development, Enable self-serve analytics, Identify AI/ML use cases, Evaluate AI/ML use cases, Design AI solutions, Build AI pipelines, Build ML pipelines, Promote responsible AI, Define AI governance frameworks, Implement AI governance frameworks, Establish model policies, Act as thought leader, Inspire cross-functional teams, Mentor cross-functional teams, Facilitate knowledge sharing, Promote technical excellence, Promote curiosity", "teamCollaboration" : "Cross-functional teams; DevOps teams; Cloud teams; BI teams; Analytics teams; Data Scientists; MLOps engineers; Product owners", "domainKnowledge" : "Data lakehouse; Streaming data; Unstructured data; Structured data; Business intelligence; Analytics engineering; Quantitative analysis; Cloud data stacks; ML frameworks; BI platforms; Statistical methods; Responsible AI; Ethical AI; Model interpretability; GenAI", "domainList" : [ "data-lakehouse", "streaming-data", "unstructured-data", "structured-data", "business-intelligence", "analytics-engineering", "quantitative-analysis", "cloud-data-stacks", "ml-frameworks", "bi-platforms", "statistical-methods", "responsible-ai", "ethical-ai", "model-interpretability", "genai" ], "domainSpecificKnowledge" : [ "Data lakehouse", "Streaming data", "Unstructured data", "Structured data", "Business intelligence", "Analytics engineering", "Quantitative analysis", "Cloud data stacks", "ML frameworks", "BI platforms", "Statistical methods", "Responsible AI", "Ethical AI", "Model interpretability", "GenAI" ], "toolProficiency" : [ "Dbt Cloud", "Fivetran", "Airflow" ], "communicationSkills" : "Stakeholder communication; Technical concepts communication", "innovationCreativity" : "Innovation", "qualificationsBasic" : "Bachelor's or Master's degree, 10+ years experience, Cloud data platforms experience, AI/ML frameworks knowledge, Governance frameworks experience, Data privacy experience, MLOps experience, Excellent communication skills, Stakeholder management skills, Lead technical teams ability", "qualificationsPreferred" : "AI / GenAI usecase delivery experience, Model interpretability experience, Regulatory compliance experience, Enterprise data modernization experience, AI transformation programs experience, Cloud data architecture certifications, AI certifications", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "About MBRDI: Mercedes-Benz Research and Development India (MBRDI), headquartered in Bengaluru with a satellite office in Pune, is the largest R&D center for Mercedes-Benz Group AG outside of Germany. Our mission is to drive innovation and excellence in automotive engineering, digitalization, and sustainable mobility solutions, shaping the future of mobility. We are seeking a visionary Data and AI Chief Architect to lead the design, development, and governance of department wide data and AI solutions. This role requires a balance of deep technical expertise, architectural vision, and the ability to inspire cross-functional teams toward a unified data and AI strategy. As a key member of the architecture and innovation team, you will shape how data is collected, transformed, and leveraged across the organization — enabling scalable data engineering pipelines, responsible AI adoption, and the delivery of intelligent business outcomes. Key Responsibilities 1. Data Architecture & Engineering Design and implement modern, scalable data architectures (data lakehouse, streaming, APIs, etc.) to support analytics and AI workloads. Oversee data ingestion, integration, and transformation processes across structured and unstructured sources. Partner with DevOps and Cloud teams to ensure data platforms meet enterprise performance, security, and compliance standards. Define best practices for metadata management, data lineage, and data quality frameworks. 2. Data Transformation & Analytics Enablement Lead the development of robust data models, pipelines, and transformations using modern tools (e.g., Spark, dbt, Kafka, Databricks, Synapse, Snowflake, etc.). Collaborate with BI and analytics teams to ensure data is clean, contextual, and analytics-ready. Enable business units to self-serve and innovate through governed data products and APIs. 3. AI Use Case Discovery & Delivery Partner with business stakeholders to identify and evaluate high-impact AI/ML use cases. Provide technical leadership in designing AI solutions — from proof of concept to production deployment. Collaborate with Data Scientists and MLOps engineers to build scalable AI and machine learning pipelines. Promote responsible AI practices ensuring transparency, fairness, and explainability in all AI initiatives. 4. AI Governance & Strategy Define and implement frameworks for AI governance, including ethical AI guidelines, model lifecycle management, and compliance. Establish policies for model versioning, monitoring, and risk assessment. Act as a thought leader on AI maturity and innovation across the organization. 5. Cross-Functional Leadership & Inspiration Inspire and mentor cross-functional teams — including engineers, analysts, and product owners — toward data-driven and AI-powered ways of working. Facilitate knowledge sharing and promote a culture of technical excellence and curiosity. Communicate complex technical concepts to non-technical stakeholders effectively. Required Qualifications Bachelor’s or Master’s degree in Computer Science, Data Engineering, AI, or a related field. 10+ years of experience in data architecture, data engineering, or AI/ML solution design. Proven experience with cloud data platforms (Azure, AWS, or GCP) and modern data stack tools. Strong knowledge of AI/ML frameworks (TensorFlow, PyTorch, Azure ML, SageMaker, etc.). Experience with governance frameworks, data privacy, and MLOps. Excellent communication and stakeholder management skills. Demonstrated ability to lead and inspire technical teams. Preferred Qualifications Experience in AI / GenAI usecase delivery , model interpretability, and regulatory compliance. Prior experience leading enterprise data modernization or AI transformation programs. Certifications in cloud data architecture or AI (e.g., Azure Data Engineer/Architect, AWS Certified Machine Learning). Why Join Us? Be part of a purpose-driven organization that’s shaping the future of mobility. Work on cutting-edge technologies and global projects. Thrive in a collaborative, diverse, and inclusive environment. Access world-class infrastructure and learning opportunities. Equal Opportunity Statement: At MBRDI, we are committed to diversity and inclusion. We welcome applications from all qualified individuals, regardless of gender, background, or ability. Mercedes-Benz Research and Development India Private Limited", "summaryDescription" : "T6_Chief Data and AI Architect at MBRDI. Skills: Data Architecture, AI, ML, Data Engineering. Design scalable data architectures. Oversee data ingestion", "createdAt" : "2026-06-14T08:27:53.793", "lastUpdated" : "2026-06-15T10:23:16.352", "ingestTimestamp" : "2026-06-14T08:27:53.793", "mongoId" : "69ce5e3b9bc74574cb677aec", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Data modeling", "Data ingestion", "Data integration", "Metadata management", "Data lineage", "Data quality", "Model lifecycle management", "Model versioning", "Model monitoring", "Risk assessment", "Data Architecture", "AI", "ML", "Data Engineering", "Solution design", "Stakeholder management", "Team leadership", "Thought leadership", "Knowledge sharing", "Technical excellence", "Data lakehouse", "Streaming data", "Unstructured data", "Structured data", "Business intelligence", "Analytics engineering", "Quantitative analysis", "Cloud data stacks", "ML frameworks", "BI platforms", "Statistical methods", "Responsible AI", "Ethical AI", "Model interpretability", "GenAI", "Azure Data Engineer", "Azure Architect", "AWS Certified Machine Learning", "Dbt Cloud", "Fivetran", "Airflow" ], "skillCount" : 41, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Executive", "dataQualityScore" : 0.8888889, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Automotive", "llmIndustryConfidence" : 0.95 }, { "id" : "6a306647f292fd229cfafc8d", "title" : "Lead Product Manager, Data and AI", "company" : "Lyra Health", "industry" : "Product", "salary" : { "min" : 161000.0, "max" : 221500.0, "currency" : "USD", "frequency" : "yearly" }, "location" : "United States", "locations" : [ "United States" ], "timestamp" : "2026-06-16T11:46:32.032", "fingerprint" : "7be737cc8ee8a6035793f5d2e69d5f06381cd02b4aff658c15d77ee3e54d1515", "source" : "lever", "language" : "en", "applyUrl" : "https://jobs.lever.co/lyrahealth/e3d731e8-eea0-4ae4-bd9a-5624b91ca129/apply", "externalId" : "e3d731e8-eea0-4ae4-bd9a-5624b91ca129", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 8, "experienceMaxYears" : 15, "experienceLevel" : "Lead", "coreResponsibilities" : "Develop product strategy, Define product roadmap, Write user stories, Collaborate with cross-functional teams", "teamCollaboration" : "Cross-functional teams", "remoteFriendly" : true, "rawDescription" : "## Description About Lyra Health Lyra Health is a leading provider of evidence-based mental health care, serving more than 20 million people globally in partnership with employers and more than 100 million through health plan and partner relationships. The company has delivered more than 15 million sessions of mental health care, published more than 35 peer-reviewed studies, and delivered unmatched outcomes in terms of access, clinical effectiveness, and cost efficiency. Extensive peer-reviewed research confirms Lyra’s transformative care model helps people recover twice as fast and results in a 26% annual reduction in overall healthcare claims costs. Lyra is transforming access to life-changing mental health care through Lyra Empower, the only fully integrated, AI-powered platform combining the highest-quality care and technology solutions. ## Responsibilities Product Vision & Strategy: Define and champion a compelling multi-year product vision and roadmap for data and AI platforms, aligning technical milestones with Lyra's business growth, revenue objectives, and clinical goals. GenAI & Modern Lifecycle Management: Drive high-impact opportunities leveraging generative AI, Large Language Models (LLMs), agentic AI, and advanced analytics, managing the entire lifecycle from ideation and rapid experimentation to scalable production deployment. Cross-Functional Leadership: Collaborate extensively across complex matrixed stakeholder groups—including Product, Design, Engineering, Clinical Quality, and GTM teams—to embed smart AI capabilities directly into core member experiences and operations. Responsible AI & Governance: Partner closely with Legal, Privacy, and Clinical leadership to maintain rigorous responsible AI practices Impact Metrics & Optimization: Design robust measurement and experimentation frameworks (such as online controlled A/B testing) to track model effectiveness, quantify business outcomes, and evaluate trade-offs between tactical execution and long-term research. Technical Team Collaboration: Translate unstructured business pain points into crisp, detailed product requirements, acting as a translator between highly technical data disciplines and non-technical business leaders. Mentorship & Culture: Lead by example, mentoring junior team members, sharing technical product management best practices, and actively fostering a highly rigorous, data-driven culture across the product organization. ## Qualifications Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related highly quantitative field. Product Experience: 8+ years (Lead PM) of progressive product management experience within successful enterprise SaaS, cloud-based software, or health tech organizations, with a proven history of launching large-scale products with complex dependencies. Data & AI Expertise: 3+ years of direct experience shipping machine learning and data-driven products at scale. Deep understanding of modern machine learning algorithms, deep learning techniques, generative AI use cases, and the infrastructure needed to deploy LLMs contextually. Communication Skills: Exceptional written and verbal communication, narrative storytelling, and presentation skills; masterful ability to communicate complex algorithmic systems and technical trade-offs to non-technical executive teams and demanding corporate customer audiences. Strategic Execution: Proven capacity to methodically unpack ambiguity, handle competing objectives, establish clear product boundaries, and maintain a calm, execution-oriented mindset in a fast-paced, high-velocity environment. Healthcare Alignment (Nice-to-Have): Prior experience navigating a highly regulated industry (Healthcare Tech, FinTech) with an innate respect for data ethics, privacy constraints, and patient clinical quality. ## Additional Information \"We are an Equal Opportunity Employer. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, age, disability, genetic information or any other category protected by law. By applying for this position, you acknowledge that your personal information will be processed as per the Lyra Health Workforce Privacy Notice. Through this application, to the extent permitted by law, we will collect personal information from you including, but not limited to, your name, email address, gender identity, employment information, and phone number for the purposes of recruiting and assessing suitability, aptitude, skills, qualifications, and interests for employment with Lyra. We may also collect information about your race, ethnicity, and sexual orientation, which is considered sensitive personal information under the California Privacy Rights Act (CPRA) and special category data under the UK and EU GDPR. Providing this information is optional and completely voluntary, and if you provide it you consent to Lyra processing it for the purposes as described at the point of collection, for example for diversity and inclusion initiatives. If you are a California resident and would like to limit how we use this information, please use the Limit the Use of My Sensitive Personal Information form. This information will only be retained for as long as needed to fulfill the purposes for which it was collected, as described above. Please note that Lyra does not “sell” or “share” personal information as defined by the CPRA. Outside of the United States, for example in the EU, Switzerland and the UK, you may have the right to request access to, or a copy of, your personal information, including in a portable format; request that we delete your information from our systems; object to or restrict processing of your information; or correct inaccurate or outdated personal information in our systems. These rights may be subject to legal limitations. To exercise your data privacy rights outside of the United States, please contact globaldpo@lyrahealth.com. For more information about how we use and retain your information, please see our Workforce Privacy Notice.\"", "summaryDescription" : "Lead Product Manager, Data and AI at Lyra Health. Develop product strategy. Define product roadmap", "postedDate" : "2026-06-15T02:55:35.385", "createdAt" : "2026-06-15T02:55:35.385", "lastUpdated" : "2026-06-16T11:46:32.032", "ingestTimestamp" : "2026-06-16T03:24:16.833", "mongoId" : "6a306647f292fd229cfafc8d", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 161000, "salaryAnnualMax" : 221500, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "product", "jobSubcategory" : "product_management", "seniorityLevel" : "Lead", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Healthcare", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2d024e74d8ee00a0abbc9d", "title" : "Data and AI Marketing Intern", "salary" : { "min" : 45000.0, "max" : 65000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for an entry-level Data and AI Marketing Intern in Alexandria, United States, adjusted for the technology industry." }, "location" : "Alexandria, VA", "locations" : [ "Alexandria, VA" ], "timestamp" : "2026-06-16T06:12:07.063", "fingerprint" : "4f4c4efce6ad0b5bd7f08cf27db19dffaac43726855640ef3a2b30d36e1a76f1", "source" : "jazzhr", "language" : "en", "externalId" : "5wjRGUZ0z4", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Alexandria", "state" : "Virginia", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "38.8051095,-77.0470229" } ], "locationText" : "Alexandria, Virginia, United States", "employmentType" : "INTERNSHIP", "experienceMinYears" : 0, "experienceMaxYears" : 2, "experienceLevel" : "Entry", "remoteFriendly" : false, "summaryDescription" : "Data and AI Marketing Intern", "createdAt" : "2026-06-14T19:12:31.506", "lastUpdated" : "2026-06-16T06:12:07.063", "ingestTimestamp" : "2026-06-14T19:12:31.506", "mongoId" : "6a2d024e74d8ee00a0abbc9d", "processingStatus" : "llm_updated", 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"a7d2ce63b5b0739ffe98855ef0345f3066560a6653365cf95983eefecd99bb51", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/rhoda-ai/c90321f2-5085-4f99-ac13-0de996ba1dd1/application", "externalId" : "c90321f2-5085-4f99-ac13-0de996ba1dd1", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Palo Alto", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "37.4443293,-122.1598465" } ], "locationText" : "Palo Alto, California, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, Cloud object storage, Databases, Metadata stores, Ray, Spark, Vision-language models, Snowflake, BigQuery, Redshift, DVC, Delta Lake", "professionalSkills" : [ "System design", "ML infrastructure", "Data infrastructure", "Distributed systems", "Production reliability", "Performance optimization", "Cost efficiency" ], "hardSkillsList" : [ "Data pipeline optimization", "Storage system optimization", "Indexing systems", "Retrieval systems", "Dataset querying", "Dataset filtering", "Dataset iteration", "Observability frameworks", "Monitoring", "Alerting", "Failure recovery", "Workload balancing", "Data artifact management", "Data versioning", "Data lineage", "Reproducibility", "Traceability", "Data exploration", "Data analysis", "ML inference" ], "hardSkills" : [ { "name" : "Data pipeline optimization", "level" : "intermediate" }, { "name" : "Storage system optimization", "level" : "intermediate" }, { "name" : "Indexing systems", "level" : "intermediate" }, { "name" : "Retrieval systems", "level" : "intermediate" }, { "name" : "Dataset querying", "level" : "intermediate" }, { "name" : "Dataset filtering", "level" : "intermediate" }, { "name" : "Dataset iteration", "level" : "intermediate" }, { "name" : "Observability frameworks", "level" : "intermediate" }, { "name" : "Monitoring", "level" : "intermediate" }, { "name" : "Alerting", "level" : "intermediate" }, { "name" : "Failure recovery", "level" : "intermediate" }, { "name" : "Workload balancing", "level" : "intermediate" }, { "name" : "Data artifact management", "level" : "intermediate" }, { "name" : "Data versioning", "level" : "intermediate" }, { "name" : "Data lineage", "level" : "intermediate" }, { "name" : "Reproducibility", "level" : "intermediate" }, { "name" : "Traceability", "level" : "intermediate" }, { "name" : "Data exploration", "level" : "intermediate" }, { "name" : "Data analysis", "level" : "intermediate" }, { "name" : "ML inference", "level" : "intermediate" } ], "majorSkills" : "Data Infrastructure, Distributed Systems, ML Infrastructure, Data Pipelines", "majorSkillsList" : [ "Data Infrastructure", "Distributed Systems", "ML Infrastructure", "Data Pipelines" ], "coreResponsibilities" : "Architect data infrastructure, Build data infrastructure, Scale data infrastructure, Process video clips, Manage video clips, Design storage systems, Optimize storage systems, Build indexing systems, Build retrieval systems, Support dataset querying, Support dataset filtering, Support dataset iteration, Develop observability frameworks, Implement workload balancing, Implement throughput optimization, Manage data artifacts, Manage data versioning, Manage data lineage, Build internal interfaces, Build lightweight tools, Enable data exploration, Enable data querying, Enable data analysis, Support integration of VLMs, Support scalable deployment of VLMs, Generate metadata", "teamCollaboration" : "Collaboration with researchers; Collaboration with engineers", "domainKnowledge" : "Generalist robotics; Foundation world models; Multimodal datasets; Robotics data formats; Real-world sensor data; Vision-language models", "domainList" : [ "generalist-robotics", "foundation-world-models", "multimodal-datasets", "robotics-data-formats", "real-world-sensor-data", "vision-language-models" ], "domainSpecificKnowledge" : [ "Generalist robotics", "Foundation world models", "Multimodal datasets", "Robotics data formats", "Real-world sensor data", "Vision-language models" ], "toolProficiency" : [ "Ray", "Spark", "DVC", "Delta Lake" ], "problemSolvingSkills" : "Performance optimization; Cost-performance tradeoffs", "qualificationsBasic" : "5+ years of experience in data infrastructure, 5+ years of experience in distributed systems, 5+ years of experience in ML infrastructure, Experience building large-scale data pipelines, Experience operating large-scale data pipelines, Deep understanding of distributed systems, Deep understanding of databases, Deep understanding of indexing strategies, Deep understanding of cloud storage architectures, Experience optimizing data throughput, Experience with workload balancing, Experience with cost-performance tradeoffs, Experience with distributed compute frameworks, Skills in observability, Skills in monitoring, Skills in production reliability, Software engineering fundamentals, Ability to own systems end-to-end", "qualificationsPreferred" : "1B+ samples data pipelines experience, Petabyte-scale systems experience, Experience managing large multimodal datasets, Familiarity with ML training workflows, Familiarity with data lifecycle management, Familiarity with vision-language models, Experience running ML inference workloads, Experience with robotics data formats, Experience with real-world sensor data, Experience with data warehouse technologies, Familiarity with data versioning tooling, Familiarity with data lineage tooling", "remoteFriendly" : false, "rawDescription" : "At Rhoda AI, we’re building the next generation of generalist intelligent robots. We own the full robotics stack from high-performance hardware and robot systems to the infrastructure and state-of-the-art foundation world models that control our robots. Our robots are designed to be generalists capable of operating in complex, real-world environments and handling long-tail edge cases, made possible by our cutting edge research and end-to-end system design. We've raised over $400M and are investing aggressively in model research, infrastructure, hardware development, and manufacturing scale-up to make generalist robotics a reality. We're looking for Data Infrastructure MLEs to scale the systems that power our model training data pipeline, from raw ingestion and storage to indexing, retrieval, and throughput optimization at massive scale. We hire across levels — from senior to staff. What You'll Do - Architect, build, and scale a high-throughput data infrastructure that processes and manages billions of video clips with strong guarantees around reliability, latency, and cost efficiency - Design and optimize large-scale storage systems (cloud object storage, databases, metadata stores) for multimodal datasets - Build efficient indexing and retrieval systems to support fast dataset querying, filtering, and iteration for research and production use cases - Develop observability frameworks for data pipelines including monitoring, alerting, failure recovery, and performance optimization - Implement intelligent workload balancing and throughput optimization across distributed compute and storage systems - Manage data artifacts, versioning, and lineage to ensure reproducibility and traceability across training runs - Build internal interfaces and lightweight tools that enable researchers and engineers to explore, query, and analyze large datasets at scale - Support integration and scalable deployment of vision-language models (VLMs) within data pipelines for screening, enrichment, or metadata generation What We're Looking For - 5+ years of experience in data infrastructure, distributed systems, ML infrastructure, or a closely related field - Strong experience building and operating large-scale data pipelines (1B+ samples or petabyte-scale systems preferred) - Deep understanding of distributed systems, databases, indexing strategies, and cloud storage architectures - Experience optimizing data throughput, workload balancing, and cost-performance tradeoffs in cloud environments - Experience with distributed compute frameworks such as Ray or Spark for large-scale data processing and transformation - Strong skills in observability, monitoring, and production reliability for high-scale systems - Strong software engineering fundamentals with the ability to own systems end-to-end, from design to production - Staff-level candidates are expected to define technical direction and own architectural decisions independently; senior candidates execute complex systems work with strong fundamentals and growing scope Nice to Have (But Not Required) - Experience managing large multimodal datasets - Familiarity with ML training workflows and data lifecycle management - Familiarity with vision-language models (VLMs) and experience running ML inference workloads at scale in distributed or cloud environments - Experience with robotics data formats or real-world sensor data (video, proprioception, teleoperation logs) - Experience with data warehouse technologies (e.g., Snowflake, BigQuery, or Redshift) for large-scale data storage, querying, and analytics - Familiarity with data versioning and lineage tooling (e.g., DVC, Delta Lake, or similar) Why This Role - Own the data foundation that everything else runs on — model quality is only as good as the data infrastructure beneath it - Direct collaboration with research and ML systems teams; your work has immediate, measurable impact on training velocity - High ownership in a small team — you'll make real architectural decisions, not execute tickets - Help build the infrastructure that powers robots operating in the real world, at scale", "summaryDescription" : "Research Engineer - Data Infrastructure at Rhoda AI. Skills: Data Infrastructure, Distributed Systems, ML Infrastructure, Data Pipelines. Architect data infrastructure. Build data infrastructure", "createdAt" : "2026-06-14T18:49:57.612", "lastUpdated" : "2026-06-16T06:05:20.878", "ingestTimestamp" : "2026-06-14T18:49:57.612", "mongoId" : "6a2ca17574d8ee00a09a5954", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 185000, "salaryAnnualMax" : 265000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Data pipeline optimization", "Storage system optimization", "Indexing systems", "Retrieval systems", "Dataset querying", "Dataset filtering", "Dataset iteration", "Observability frameworks", "Monitoring", "Alerting", "Failure recovery", "Workload balancing", "Data artifact management", "Data versioning", "Data lineage", "Reproducibility", "Traceability", "Data exploration", "Data analysis", "ML inference", "Data Infrastructure", "Distributed Systems", "ML Infrastructure", "Data Pipelines", "System design", "ML infrastructure", "Data infrastructure", "Distributed systems", "Production reliability", "Performance optimization", "Cost efficiency", "Generalist robotics", "Foundation world models", "Multimodal datasets", "Robotics data formats", "Real-world sensor data", "Vision-language models", "Ray", "Spark", "DVC", "Delta Lake" ], "skillCount" : 41, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Senior", "dataQualityScore" : 0.8888889, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a305819f292fd229cf40436", "title" : "Contingent Research Data Analyst, HEOR", "company" : "Intuitive", "industry" : "Medical Device", "salary" : { "min" : 1000000.0, "max" : 1500000.0, "currency" : "TWD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a mid-seniority Contingent Research Data Analyst in Healthcare in Taipei, Taiwan, adjusted for company size and industry." }, "location" : "Taipei, TAIWAN, TW", "locations" : [ "Taipei", "TAIWAN", "TW" ], "certifications" : [ "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified" ], "timestamp" : "2026-06-16T07:23:29.767", "fingerprint" : "a35e775eaa33eafe9549030a7abec1a38573d3894f3dc70a602e9b377099b2ec", "source" : "smartrecruiters", "language" : "en", "applyUrl" : "https://jobs.smartrecruiters.com/Intuitive/744000132196718-contingent-research-data-analyst-heor", "externalId" : "744000132196718", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Taipei", "country" : "Taiwan", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "25.0375198,121.5636796" } ], "locationText" : "Taipei, Taiwan", "employmentType" : "CONTRACT", "experienceMinYears" : 2, "experienceMaxYears" : 5, "experienceLevel" : "mid", "technicalSkills" : "SQL, Python, R, Spark, Dbt, Snowflake, BigQuery, Redshift, Databricks, Fivetran, Airflow, Delta Lake, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow, AWS, GCP, Azure, SageMaker, Vertex AI, ML Studio", "professionalSkills" : [ "Data analysis", "Data engineering", "Machine learning", "Business intelligence", "Analytics engineering", "Quantitative analysis", "Statistical methods", "Modelling skills" ], "hardSkillsList" : [ "Statistical analysis", "Data modelling", "Machine learning modelling", "A/B testing", "Causal inference" ], "hardSkills" : [ { "name" : "Statistical analysis", "level" : "intermediate" }, { "name" : "Data modelling", "level" : "intermediate" }, { "name" : "Machine learning modelling", "level" : "intermediate" }, { "name" : "A/B testing", "level" : "intermediate" }, { "name" : "Causal inference", "level" : "intermediate" } ], "majorSkills" : "Data analysis, Machine learning, Data engineering", "majorSkillsList" : [ "Data analysis", "Machine learning", "Data engineering" ], "coreResponsibilities" : "Perform data analysis, Develop data models, Build and maintain data pipelines, Implement machine learning models, Create business intelligence dashboards, Collaborate with cross-functional teams, Communicate findings to stakeholders", "teamCollaboration" : "Cross-functional teams; Stakeholders", "toolProficiency" : [ "Tableau", "Power BI", "Looker" ], "communicationSkills" : "Communicate findings", "problemSolvingSkills" : "Problem solving", "qualificationsBasic" : "5+ years of experience in data analysis, Proficiency in SQL, Bachelor's degree in Statistics, Mathematics, Computer Science, or related field", "qualificationsPreferred" : "PhD preferred, Experience with Python or R, Experience with cloud platforms (AWS, GCP, Azure), Experience with ML frameworks (scikit-learn, TensorFlow, PyTorch), GCP Professional Data Engineer certification, AWS Data Analytics certification, Databricks Certified certification, Dbt Certified certification", "remoteFriendly" : false, "rawDescription" : "At Intuitive, we are united behind our mission: we believe that minimally invasive care is life-enhancing care. Through ingenuity and intelligent technology, we expand the potential of physicians to heal without constraints. As a pioneer and market leader in robotic-assisted surgery, we strive to foster an inclusive and diverse team, committed to making a difference. For more than 25 years, we have worked with hospitals and care teams around the world to help solve some of healthcare's hardest challenges and advance what is possible. Intuitive has been built by the efforts of great people from diverse backgrounds. We believe great ideas can come from anywhere. We strive to foster an inclusive culture built around diversity of thought and mutual respect. We lead with inclusion and empower our team members to do their best work as their most authentic selves. Passionate people who want to make a difference drive our culture. Our team members are grounded in integrity, have a strong capacity to learn, the energy to get things done, and bring diverse, real world experiences to help us think in new ways. We actively invest in our team members to support their long-term growth so they can continue to advance our mission and achieve their highest potential. Join a team committed to taking big leaps forward for a global community of healthcare professionals and their patients. Together, let's advance the world of minimally invasive care. Primary Function of Position: The Contingent Research Data Analyst, based out of Taiwan, will provide research, analytic, and data management support to the Ion Custom Hospital Analytics (Ion CHA) team. Ion CHA uses hospital-provided patient care data to assess the impact of the Ion lung biopsy platform on their lung cancer treatment programs. The research analyst, based out of Taiwan, will work remotely with health services researchers and market access specialists to generate research questions, and will then be expected to answer those questions by independently analyzing healthcare data. The research analyst will also support data cleaning and visualization activities for Ion CHA. Roles & Responsibilities:  Hypothesis Generation o Generate research questions related to lung cancer biopsy and treatment outcomes, costs, and other healthcare metrics. o Create statistical analysis plans to derive insights from electronic health record and other large health care databases to answer research questions. o Support evidence generation by conducting statistical analyses and writing research abstracts and publications.  Data Management, Analysis, and Visualization o Using a scripting language such as R, write code to clean data, create derived variables, merge/join/concatenate tables, identify missing values and outliers, and identify data inconsistencies. o Create data dashboards highlighting key healthcare outcome metrics by leveraging tools such as Tableau, R-Shiny, Quarto, ggplot2, and plotly. o Develop automated reports to share with internal and external stakeholders, including market access specialists and hospital executives.  Additional Project Support o As needed support GAVE team with additional data analytic and visualization projects based on analyst interests and team needs. ## Qualifications Skills, Experience, Education, & Training:  Master’s degree in biostatistics/statistics, epidemiology, or health services research.  Strong understanding of real-world data sources (i.e. medical claims data, EHR data) and observational research design.  Experience conducting analyses for healthcare research and writing abstracts/publications.  Ability to program with a scripting language such as R and Python and to query large databases using SQL.  Must reside in Taiwan. ## Additional Information Intuitive is an Equal Employment Opportunity Employer. We provide equal employment opportunities to all qualified applicants and employees, and prohibit discrimination and harassment of any type, without regard to race, sex, pregnancy, sexual orientation, gender identity, national origin, color, age, religion, protected veteran or disability status, genetic information or any other status protected under federal, state, or local applicable laws. We will consider for employment qualified applicants with arrest and conviction records in accordance with fair chance laws. U.S. Export Controls Disclaimer: In accordance with the U.S. Export Administration Regulations (15 CFR §743.13(b)), some roles at Intuitive Surgical may be subject to U.S. export controls for prospective employees who are nationals from countries currently on embargo or sanctions status. Certain information you provide as part of the application will be used for purposes of determining whether Intuitive Surgical will need to (i) obtain an export license from the U.S. Government on your behalf (note: the government’s licensing process can take 3 to 6+ months) or (ii) implement a Technology Control Plan (“TCP”) (note: typically adds 2 weeks to the hiring process). For any Intuitive role subject to export controls, final offers are contingent upon obtaining an approved export license and/or an executed TCP prior to the prospective employee’s start date, which may or may not be flexible, and within a timeframe that does not unreasonably impede the hiring need. If applicable, candidates will be notified and instructed on any requirements for these purposes. This position may be filled at a different job level than listed here depending on business need and/or on the selected candidate’s experience, knowledge and skills. Compensation will be based primarily on the job level at which the role is filled and the candidate’s qualifications, consistent with applicable law.", "summaryDescription" : "Contingent Research Data Analyst, HEOR at Intuitive. Skills: Data analysis, Machine learning, Data engineering. Perform data analysis. Develop data models", "postedDate" : "2026-06-15T12:57:57.000", "createdAt" : "2026-06-15T23:41:18.554", "lastUpdated" : "2026-06-16T07:23:29.767", "ingestTimestamp" : "2026-06-15T23:41:18.554", "mongoId" : "6a305819f292fd229cf40436", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Statistical analysis", "Data modelling", "Machine learning modelling", "A/B testing", "Causal inference", "Data analysis", "Machine learning", "Data engineering", "Business intelligence", "Analytics engineering", "Quantitative analysis", "Statistical methods", "Modelling skills", "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified", "Tableau", "Power BI", "Looker" ], "skillCount" : 20, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Mid", "dataQualityScore" : 1.0, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Healthcare", "llmIndustryConfidence" : 0.95 }, { "id" : "6a305003f292fd229ceebc59", "title" : "Contingent Research Data Analyst, HEOR", "company" : "Intuitive", "industry" : "Medical Device", "salary" : { "min" : 1050000.0, "max" : 1550000.0, "currency" : "TWD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Mid-level Contingent Research Data Analyst in Healthcare in Taipei, Taiwan, adjusted for company size and industry." }, "location" : "Taipei, TAIWAN, TW", "locations" : [ "Taipei", "TAIWAN", "TW" ], "certifications" : [ "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified" ], "timestamp" : "2026-06-16T08:47:08.504", "fingerprint" : "f93a8c378c70045e2fcbe5c4a664470518399553da229bf3c789923abd7c40ce", "source" : "smartrecruiters", "language" : "en", "applyUrl" : "https://jobs.smartrecruiters.com/Intuitive/744000132196718-contingent-research-data-analyst-heor", "externalId" : "744000132196718", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Taipei", "country" : "Taiwan", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "25.0375198,121.5636796" } ], "locationText" : "Taipei, Taiwan", "employmentType" : "CONTRACT", "experienceMinYears" : 2, "experienceMaxYears" : 5, "experienceLevel" : "mid", "technicalSkills" : "SQL, Python, R, Spark, Snowflake, BigQuery, Redshift, Databricks, Tableau, Power BI, Looker, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow, AWS, GCP, Azure", "professionalSkills" : [ "Data analysis", "Data modeling", "Statistical analysis", "Machine learning", "Business intelligence", "Data engineering", "Quantitative analysis" ], "hardSkillsList" : [ "Statistical modeling", "Machine learning algorithms", "Data wrangling", "Data visualization", "Database management", "Cloud computing", "ETL processes", "A/B testing", "Causal inference" ], "hardSkills" : [ { "name" : "Statistical modeling", "level" : "intermediate" }, { "name" : "Machine learning algorithms", "level" : "intermediate" }, { "name" : "Data wrangling", "level" : "intermediate" }, { "name" : "Data visualization", "level" : "intermediate" }, { "name" : "Database management", "level" : "intermediate" }, { "name" : "Cloud computing", "level" : "intermediate" }, { "name" : "ETL processes", "level" : "intermediate" }, { "name" : "A/B testing", "level" : "intermediate" }, { "name" : "Causal inference", "level" : "intermediate" } ], "majorSkills" : "Data Science, Data Engineering, Machine Learning, Business Intelligence", "majorSkillsList" : [ "Data Science", "Data Engineering", "Machine Learning", "Business Intelligence" ], "coreResponsibilities" : "Develop and implement data models, Build and maintain data pipelines, Perform data analysis and interpretation, Develop machine learning models, Create business intelligence dashboards, Collaborate with stakeholders, Present findings and recommendations, Ensure data quality and integrity, Stay updated on industry trends", "teamCollaboration" : "Cross-functional teams; Stakeholders; Product managers; Engineering teams", "domainKnowledge" : "Health Economics; Real-World Evidence; HEOR data", "domainList" : [ "health-economics", "real-world-evidence", "heor-data" ], "domainSpecificKnowledge" : [ "Health Economics", "Real-World Evidence", "HEOR data" ], "toolProficiency" : [ "SQL", "Python", "R", "Spark", "Snowflake", "BigQuery", "Redshift", "Databricks", "Tableau", "Power BI", "Looker", "Scikit-learn", "TensorFlow", "PyTorch", "XGBoost", "LightGBM", "Hugging Face", "MLflow", "AWS", "GCP", "Azure" ], "communicationSkills" : "Present findings; Communicate insights", "continuousLearning" : "Stay updated on industry trends", "problemSolvingSkills" : "Data analysis; Statistical modeling; Machine learning", "qualificationsBasic" : "Bachelor's degree, 3+ years of experience, Experience with SQL, Experience with Python", "qualificationsPreferred" : "Master's degree preferred, PhD preferred, Experience with R, Experience with statistical modeling, Experience with machine learning, Experience with data visualization tools, Experience with cloud platforms, Experience with HEOR data", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "At Intuitive, we are united behind our mission: we believe that minimally invasive care is life-enhancing care. Through ingenuity and intelligent technology, we expand the potential of physicians to heal without constraints. As a pioneer and market leader in robotic-assisted surgery, we strive to foster an inclusive and diverse team, committed to making a difference. For more than 25 years, we have worked with hospitals and care teams around the world to help solve some of healthcare's hardest challenges and advance what is possible. Intuitive has been built by the efforts of great people from diverse backgrounds. We believe great ideas can come from anywhere. We strive to foster an inclusive culture built around diversity of thought and mutual respect. We lead with inclusion and empower our team members to do their best work as their most authentic selves. Passionate people who want to make a difference drive our culture. Our team members are grounded in integrity, have a strong capacity to learn, the energy to get things done, and bring diverse, real world experiences to help us think in new ways. We actively invest in our team members to support their long-term growth so they can continue to advance our mission and achieve their highest potential. Join a team committed to taking big leaps forward for a global community of healthcare professionals and their patients. Together, let's advance the world of minimally invasive care. Primary Function of Position: The Contingent Research Data Analyst, based out of Taiwan, will provide research, analytic, and data management support to the Ion Custom Hospital Analytics (Ion CHA) team. Ion CHA uses hospital-provided patient care data to assess the impact of the Ion lung biopsy platform on their lung cancer treatment programs. The research analyst, based out of Taiwan, will work remotely with health services researchers and market access specialists to generate research questions, and will then be expected to answer those questions by independently analyzing healthcare data. The research analyst will also support data cleaning and visualization activities for Ion CHA. Roles & Responsibilities:  Hypothesis Generation o Generate research questions related to lung cancer biopsy and treatment outcomes, costs, and other healthcare metrics. o Create statistical analysis plans to derive insights from electronic health record and other large health care databases to answer research questions. o Support evidence generation by conducting statistical analyses and writing research abstracts and publications.  Data Management, Analysis, and Visualization o Using a scripting language such as R, write code to clean data, create derived variables, merge/join/concatenate tables, identify missing values and outliers, and identify data inconsistencies. o Create data dashboards highlighting key healthcare outcome metrics by leveraging tools such as Tableau, R-Shiny, Quarto, ggplot2, and plotly. o Develop automated reports to share with internal and external stakeholders, including market access specialists and hospital executives.  Additional Project Support o As needed support GAVE team with additional data analytic and visualization projects based on analyst interests and team needs. ## Qualifications Skills, Experience, Education, & Training:  Master’s degree in biostatistics/statistics, epidemiology, or health services research.  Strong understanding of real-world data sources (i.e. medical claims data, EHR data) and observational research design.  Experience conducting analyses for healthcare research and writing abstracts/publications.  Ability to program with a scripting language such as R and Python and to query large databases using SQL.  Must reside in Taiwan. ## Additional Information Intuitive is an Equal Employment Opportunity Employer. We provide equal employment opportunities to all qualified applicants and employees, and prohibit discrimination and harassment of any type, without regard to race, sex, pregnancy, sexual orientation, gender identity, national origin, color, age, religion, protected veteran or disability status, genetic information or any other status protected under federal, state, or local applicable laws. We will consider for employment qualified applicants with arrest and conviction records in accordance with fair chance laws. U.S. Export Controls Disclaimer: In accordance with the U.S. Export Administration Regulations (15 CFR §743.13(b)), some roles at Intuitive Surgical may be subject to U.S. export controls for prospective employees who are nationals from countries currently on embargo or sanctions status. Certain information you provide as part of the application will be used for purposes of determining whether Intuitive Surgical will need to (i) obtain an export license from the U.S. Government on your behalf (note: the government’s licensing process can take 3 to 6+ months) or (ii) implement a Technology Control Plan (“TCP”) (note: typically adds 2 weeks to the hiring process). For any Intuitive role subject to export controls, final offers are contingent upon obtaining an approved export license and/or an executed TCP prior to the prospective employee’s start date, which may or may not be flexible, and within a timeframe that does not unreasonably impede the hiring need. If applicable, candidates will be notified and instructed on any requirements for these purposes. This position may be filled at a different job level than listed here depending on business need and/or on the selected candidate’s experience, knowledge and skills. Compensation will be based primarily on the job level at which the role is filled and the candidate’s qualifications, consistent with applicable law.", "summaryDescription" : "Contingent Research Data Analyst, HEOR at Intuitive. Skills: Data Science, Data Engineering, Machine Learning, Business Intelligence. Develop and implement data models. Build and maintain data pipelines", "postedDate" : "2026-06-15T12:57:57.000", "createdAt" : "2026-06-15T21:38:55.159", "lastUpdated" : "2026-06-16T08:47:08.504", "ingestTimestamp" : "2026-06-15T21:38:55.159", "mongoId" : "6a305003f292fd229ceebc59", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Statistical modeling", "Machine learning algorithms", "Data wrangling", "Data visualization", "Database management", "Cloud computing", "ETL processes", "A/B testing", "Causal inference", "Data Science", "Data Engineering", "Machine Learning", "Business Intelligence", "Data analysis", "Data modeling", "Statistical analysis", "Machine learning", "Business intelligence", "Data engineering", "Quantitative analysis", "Health Economics", "Real-World Evidence", "HEOR data", "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified", "SQL", "Python", "R", "Spark", "Snowflake", "BigQuery", "Redshift", "Databricks", "Tableau", "Power BI", "Looker", "Scikit-learn", "TensorFlow", "PyTorch", "XGBoost", "LightGBM", "Hugging Face", "MLflow", "AWS", "GCP", "Azure" ], "skillCount" : 48, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Mid", "dataQualityScore" : 1.0, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Healthcare", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6a8f74d8ee00a090c9ce", "title" : "Sr Director, Data and Application Engineering", "company" : "ABACUS", "industry" : "Technology", "salary" : { "min" : 245000.0, "max" : 375000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline data for a Sr Director, Data and Application Engineering in the Technology industry in the United States, adjusted for seniority and remote work." }, "location" : "Remote in US", "locations" : [ "Remote in US" ], "timestamp" : "2026-06-15T21:47:59.306", "fingerprint" : "7470b233e5544201af654abb5b65c275bc32fcf3e35253199982be98ed3b7f16", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://abacustechnology.com/about/careers/current-vacancies/?gh_jid=7726360003", "externalId" : "7726360003", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "FULL_TIME", "experienceLevel" : "Director", "technicalSkills" : "AI/ML, Data platform, DevOps, Application Development, CI/CD, Automation tooling, ServiceNow development, ServiceNow configuration, AI-powered tools, AI agents", "professionalSkills" : [ "Strategic leadership", "Execution focus", "Technical strategy", "Stakeholder management", "Organizational design", "Team development", "Cross-functional collaboration", "Executive communication" ], "hardSkillsList" : [ "Metrics definition", "KPI tracking", "Risk reporting", "Outcome reporting", "Governance standards", "Compliance standards", "Security standards" ], "softSkillsList" : [ "Leadership" ], "hardSkills" : [ { "name" : "Metrics definition", "level" : "intermediate" }, { "name" : "KPI tracking", "level" : "intermediate" }, { "name" : "Risk reporting", "level" : "intermediate" }, { "name" : "Outcome reporting", "level" : "intermediate" }, { "name" : "Governance standards", "level" : "intermediate" }, { "name" : "Compliance standards", "level" : "intermediate" }, { "name" : "Security standards", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" } ], "majorSkills" : "Data Engineering, Application Development, DevOps, AI Development", "majorSkillsList" : [ "Data Engineering", "Application Development", "DevOps", "AI Development" ], "coreResponsibilities" : "Lead technical teams, Drive engineering initiatives, Oversee practice areas, Align teams to goals, Ensure rigorous practices, Ensure velocity, Ensure collaboration, Build enterprise-grade platforms, Build enterprise-grade solutions, Support career development, Define KPIs, Track KPIs, Report progress, Report risks, Report outcomes, Ensure practices meet governance, Ensure practices meet compliance, Ensure practices meet security, Architect enterprise data platform, Resource enterprise data platform, Deliver data platform capabilities, Structure ServiceNow backlog, Prioritize ServiceNow backlog, Progress ServiceNow development, Identify DevOps automation initiatives, Scope DevOps automation initiatives, Deliver DevOps automation efficiency, Own Abacus portal roadmap, Communicate Abacus portal roadmap, Progress Abacus portal development, Deploy AI solutions, Deliver AI business value, Define team charters, Define team goals, Define team delivery metrics, Reflect cross-team collaboration, Reflect consistent delivery", "teamCollaboration" : "Cross-functional teams; Internal stakeholders; Executive leadership; Service delivery team; Across multiple disciplines", "projectManagementSkills" : [ "Roadmap planning", "Prioritization" ], "domainKnowledge" : "Regulated environments; Financial services; Healthcare; Managed Services Provider (MSP); ITSM platforms; Data lakes; Lakehouses; Data mesh architectures", "domainList" : [ "regulated-environments", "financial-services", "healthcare", "managed-services-provider-msp", "itsm-platforms", "data-lakes", "lakehouses", "data-mesh-architectures" ], "domainSpecificKnowledge" : [ "Regulated environments", "Financial services", "Healthcare", "Managed Services Provider (MSP)", "ITSM platforms", "Data lakes", "Lakehouses", "Data mesh architectures" ], "toolProficiency" : [ "ServiceNow" ], "communicationSkills" : "Executive communication; Stakeholder management; Compelling communication", "continuousLearning" : "Online courses", "outcomesObjectives" : "Enterprise data platform foundation architected; Enterprise data platform resourced; Enterprise data platform delivering capabilities; ServiceNow development backlog progressing; DevOps automation delivering efficiency; Abacus portal roadmap progressing; AI solutions deployed; AI solutions delivering value; Teams operate with clear charters; Teams operate with clear goals; Teams operate with clear metrics; Engineering culture reflects collaboration; Engineering culture reflects delivery", "qualificationsBasic" : "12+ years software engineering, data engineering, DevOps, 7+ years progressive engineering leadership, Managing managers or multi-team organizations, Delivering enterprise-scale platforms and applications, Working in regulated industries, Translate business objectives into technical strategy", "qualificationsPreferred" : "Experience in Managed Services Provider (MSP), Familiarity with ServiceNow development and configuration, Hands-on data platform architecture, Hands-on AI/ML engineering, Hands-on DevOps automation, Experience with AI governance frameworks, Experience with risk management frameworks, Experience with compliance frameworks, Exposure to enterprise data platform design", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Overview We are seeking a highly strategic and execution-focused Sr Director, Data and Application Engineering to lead a broad portfolio of technical teams driving the organization's most critical engineering initiatives. Reporting directly to the Chief Technology Officer (CTO), this leader will oversee four core practice areas — DevOps, Application Development, Data Engineering, and Internal AI Development — and will be responsible for aligning these teams to deliver on the department's strategic goals. As a 1,000-person Managed Services Provider (MSP) serving financial services and healthcare clients, we operate in highly regulated environments that demand secure, compliant, and reliable engineering practices. This leader will ensure all teams operate with the rigor, velocity, and collaboration required to build enterprise-grade platforms and solutions. Reporting Structure Reports to: Chief Technology Officer (CTO) Direct Reports: Engineering leads across DevOps, Application Development, Data Engineering, and AI Development Teams Overseen DevOps Responsible for the infrastructure, CI/CD pipelines, and internal automation capabilities of the organization. This team supports development velocity, reliability, and the continued expansion of automation tooling across internal operations. Application Development Owns the design, development, and ongoing maintenance of internally built applications — most notably the Abacus portal — and supports service delivery initiatives including development and configuration work within ServiceNow. Data Engineering Leads the architecture, construction, and operation of the organization's enterprise data platform, enabling reliable, governed, and scalable data infrastructure across business units. Internal AI Development Drives the development and deployment of AI-powered tools and agents that deliver measurable efficiency gains across the organization. Partners with internal stakeholders to identify, prioritize, and implement AI solutions aligned to business needs. Departmental Goals This role is accountable for organizing and directing all four teams toward the following high-level department objectives: Build and mature the organization's enterprise data platform to support scalable, governed, and insight-ready data infrastructure Assist the service delivery team with the continued development and configuration of ServiceNow to improve ITSM capabilities and operational workflows Expand and integrate the DevOps team's scope to encompass internal automation initiatives, reducing manual effort and improving engineering efficiency across the organization Own the roadmap, development, and ongoing evolution of the internally developed Abacus portal Collaborate with internal stakeholders to identify, prioritize, and deliver AI solutions that drive organizational efficiency and support strategic business outcomes Key Responsibilities Strategic Leadership support career development at all levels Metrics, Reporting & Governance Define and track KPIs across teams (e.g., deployment frequency, platform uptime, data quality, AI adoption, development velocity) Regularly report progress, risks, and outcomes to the CTO and executive leadership Ensure all engineering practices meet governance, compliance, and security standards for regulated environments Qualifications Required 12+ years of experience in software engineering, data engineering, DevOps, or related technical disciplines 7+ years in progressive engineering leadership roles, including managing managers or multi-team organizations Demonstrated experience overseeing multiple, diverse technical teams simultaneously Proven track record of delivering enterprise-scale platforms and applications in production environments Experience working in regulated industries such as financial services, healthcare, or similar Strong ability to translate business objectives into technical strategy and measurable delivery outcomes Excellent executive communication and stakeholder management skills Preferred Experience within a Managed Services Provider (MSP) or services-based technology organization Familiarity with ITSM platforms, particularly ServiceNow development and configuration Hands-on background in one or more of: data platform architecture, AI/ML engineering, or DevOps automation Experience with AI governance, risk management, and compliance frameworks Exposure to enterprise data platform design (e.g., data lakes, lakehouses, data mesh architectures) Key Competencies Strategic vision balanced with pragmatic execution Cross-functional collaboration and executive stakeholder management Organizational design and team development across multiple disciplines Data-driven decision-making and outcomes orientation Clear, compelling communication with both technical and non-technical audiences Ability to lead through ambiguity in a fast-paced, evolving environment Success Metrics (First 12–18 Months) Enterprise data platform foundation is architected, resourced, and delivering initial capabilities ServiceNow development backlog is structured, prioritized, and progressing in partnership with service delivery DevOps automation initiatives are identified, scoped, and delivering measurable efficiency gains Abacus portal roadmap is owned, communicated, and actively progressing At least 2–3 AI solutions are deployed and delivering measurable business value All four engineering teams operate with clear charters, goals, and delivery metrics Engineering culture reflects strong cross-team collaboration and consistent delivery practices Why This Role Matters This role sits at the intersection of platform, product, data, and AI — and is central to the organization's ability to scale, innovate, and operate with excellence. The Senior Director of Engineering will unify four critical engineering functions under a shared vision, accelerating the delivery of the enterprise data platform, modernizing internal tooling, and embedding AI-driven efficiency into the organization's core operations. This is a high-visibility, high-impact leadership role with direct line of sight to the CTO and meaningful influence over the company's long-term technical direction. Benefits of Working for Abacus: Exposure to diverse array of technologies Part of a team of experienced engineers who aim to deliver exceptional service Competitive compensation Performance bonus Robust benefits package: medical, dental, vision, disability, life insurance, 401k, and PTO Opportunities to further technical education through online courses Positive, friendly, supportive work environment", "summaryDescription" : "Sr Director, Data and Application Engineering at ABACUS. Skills: Data Engineering, Application Development, DevOps, AI Development. 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ML frameworks; BI platforms; Cloud data stacks", "domainList" : [ "cloud-data-services", "ml-frameworks", "bi-platforms", "cloud-data-stacks" ], "domainSpecificKnowledge" : [ "Cloud data services", "ML frameworks", "BI platforms", "Cloud data stacks" ], "toolProficiency" : [ "Tableau", "Power BI", "Looker", "Metabase", "Superset", "Qlik", "MicroStrategy" ], "qualificationsBasic" : "5+ years experience, SQL proficiency", "qualificationsPreferred" : "PhD preferred, GCP Professional Data Engineer certification, AWS Data Analytics certification, Databricks Certified certification, Dbt Certified certification", "remoteFriendly" : false, "workSiteFlexibility" : "Flexible", "rawDescription" : "Job Title: Project Lead - Data and Analytics We are seeking a results-driven Project Lead Consultant to lead client-facing Data and AI initiatives from discovery through delivery. 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Manage initiatives from discovery", "createdAt" : "2026-06-14T03:13:45.271", "lastUpdated" : "2026-06-15T09:19:11.588", "ingestTimestamp" : "2026-06-14T03:13:45.271", "mongoId" : "69cf19022beec4dd3d8f336b", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 135000, "salaryAnnualMax" : 185000, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ "Data science", "Data engineering", "ML/AI", "Business intelligence", "Analytics engineering", "Quantitative analysis", "Statistical methods", "ML frameworks", "BI platforms", "Cloud data stacks", "Modelling skills", "Regression", "Classification", "Clustering", "Time-series analysis", "A/B testing", "Causal inference", "Leadership", "Project leadership", "Business analysis", "Stakeholder management", "Cloud data services", "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified", "Tableau", "Power BI", "Looker", "Metabase", "Superset", "Qlik", "MicroStrategy" ], "skillCount" : 33, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Lead", "dataQualityScore" : 0.8888889, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Consulting", "llmIndustryConfidence" : 0.95 }, { "id" : "6a3055f1f292fd229cf23389", "title" : "Support and Data Operations Associate (Fixed-term)", "company" : "Foursquare", "industry" : "Finance", "salary" : { "min" : 1000000.0, "max" : 1500000.0, "currency" : "EUR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Junior Support and Data Operations Associate in Belgrade, Serbia, adjusted for the technology industry and company size." }, "location" : "Serbia", "locations" : [ "Serbia" ], "certifications" : [ "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified" ], "timestamp" : "2026-06-16T08:56:17.647", "fingerprint" : "aaf5559b6dd261874f5f77a1afd61a6fd75d245824898322671fec42e45798b8", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/foursquare/b98303fd-481a-4f08-9feb-451f7c9b179e/application", "externalId" : "b98303fd-481a-4f08-9feb-451f7c9b179e", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Belgrade", "country" : "Serbia", "continent" : "eu", "source" : "llm", "workMode" : "hybrid", "geo" : "44.8153318,20.4456588" } ], "locationText" : "Belgrade, Serbia", "employmentType" : "FULL_TIME", "technicalSkills" : "SQL, Python, R, Scala, Spark, Dbt, Tableau, Power BI, Looker, Metabase, Superset, Qlik, MicroStrategy, Snowflake, BigQuery, Redshift, Databricks, Fivetran, Airflow, Dbt Cloud, Delta Lake, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow, AWS, GCP, Azure, S3, Glue, SageMaker, Athena, Vertex AI, Synapse, ML Studio", "professionalSkills" : [ "Data engineering", "Machine learning", "Business intelligence", "Data analytics", "Quantitative analysis", "Data modelling" ], "hardSkillsList" : [ "Statistical methods", "ML frameworks", "BI platforms", "Cloud data stacks", "Modelling skills", "Regression", "Classification", "Clustering", "Time-series analysis", "A/B testing", "Causal inference" ], "hardSkills" : [ { "name" : "Statistical methods", "level" : "intermediate" }, { "name" : "ML frameworks", "level" : "intermediate" }, { "name" : "BI platforms", "level" : "intermediate" }, { "name" : "Cloud data stacks", "level" : "intermediate" }, { "name" : "Modelling skills", "level" : "intermediate" }, { "name" : "Regression", "level" : "intermediate" }, { "name" : "Classification", "level" : "intermediate" }, { "name" : "Clustering", "level" : "intermediate" }, { "name" : "Time-series analysis", "level" : "intermediate" }, { "name" : "A/B testing", "level" : "intermediate" }, { "name" : "Causal inference", "level" : "intermediate" } ], "majorSkills" : "Data science, Data engineering, Machine learning, Business intelligence", "majorSkillsList" : [ "Data science", "Data engineering", "Machine learning", "Business intelligence" ], "toolProficiency" : [ "SQL", "Python", "R", "Scala", "Spark", "Dbt", "Tableau", "Power BI", "Looker", "Metabase", "Superset", "Qlik", "MicroStrategy", "Snowflake", "BigQuery", "Redshift", "Databricks", "Fivetran", "Airflow", "Dbt Cloud", "Delta Lake", "Scikit-learn", "TensorFlow", "PyTorch", "XGBoost", "LightGBM", "Hugging Face", "MLflow", "AWS", "GCP", "Azure", "S3", "Glue", "SageMaker", "Athena", "Vertex AI", "Synapse", "ML Studio" ], "qualificationsBasic" : "SQL proficiency, 5+ years of experience", "qualificationsPreferred" : "PhD preferred, GCP Professional Data Engineer certification, AWS Data Analytics certification, Databricks Certified certification, Dbt Certified certification, Experience with scikit-learn, Experience with TensorFlow, Experience with PyTorch, Experience with XGBoost, Experience with LightGBM, Experience with Hugging Face, Experience with MLflow, Experience with Snowflake, Experience with BigQuery, Experience with Redshift, Experience with Databricks, Experience with dbt, Experience with Fivetran, Experience with Airflow, Experience with dbt Cloud, Experience with Delta Lake, Experience with AWS SageMaker, Experience with GCP Vertex AI, Experience with Azure ML Studio", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "About Foursquare Foursquare is the leading independent location technology and data cloud platform, helping businesses connect the digital and physical worlds with precision and purpose. Our products power everything from market analytics to targeted experiences, relied on by some of the world’s most iconic brands. But what makes Foursquare truly special is how we work. We're a team of builders, problem-solvers, and collaborators who care deeply about impact – both in the products we ship and the way we show up for each other. Great outcomes come from strong collaboration and shared ownership, and we believe growth happens through real challenges – whether that’s leveling up a skill, tackling unfamiliar problems, or pushing a project forward in a new way. If you're excited by cutting-edge tech and a culture that values both autonomy and teamwork, you’ll thrive here. About the Position Foursquare is looking for a Support and Data Operations Associate to join our team in our Belgrade office; on a hybrid schedule of Tuesday, Wednesday, Thursday in office. We are looking for an inquisitive, adaptable, and highly motivated Data Support Associate to join our team. In this role, you will be primarily focused on executing web crawls, manipulating data, and utilizing internal pipeline tools to ensure data quality and availability. This is an internally focused, highly technical role where persistence, vigilance, and the ability to learn and iterate quickly are essential. If you enjoy solving technical puzzles, building and maintaining data flows, and continuously learning new skills, we want you on our team! Please note that this is a fixed-term position for an initial period of one year, with the possibility of extension. In this role, you’ll - Web Crawling & Extraction: Execute and manage web crawling initiatives, extracting data, and adapting quickly when target site structures change. - Data Manipulation & Pipelines: Utilize internal tools to perform data cleanup, matching, and transformations to ensure high data quality and reliability. - Technical Troubleshooting: Be vigilant in monitoring data pipelines; investigate issues, read and interpret log files, implement workarounds, and escalate complex technical problems. - Continuous Improvement: Learn and adapt to new internal tools and technical processes rapidly, iterating on existing workflows to improve efficiency. - Documentation: Create and maintain technical process documentation and how-to guides to empower internal teams What you’ll need - Proficient level of written and verbal English - 1+ years of experience working in data-oriented customer operations, technical support, analytics, or similar roles. - Proficiency in Python or Scala, with strong SQL skills. - Proficiency in Regular Expressions (Regex) for pattern matching, data extraction, validation, and web content processing. - Familiarity with data analysis tools and libraries (e.g., PySpark, pandas), web crawling concepts and execution. - General technical troubleshooting skills: ability to read/interpret/transform log files, comfort navigating command-line interfaces (CLI) and APIs, and a strong capacity for independent research. - Your own unique talents! If you don’t meet 100% of the qualifications outlined above, we encourage and welcome you to still apply! Benefits and Perks - 25 days of paid vacation – take the time you need to rest and recharge - Private medical insurance – comprehensive coverage for you and your family - FitPass – flexible access to gyms, wellness classes, and sports facilities across Serbia - Hybrid work schedule – in-person collaboration Tuesday–Thursday, with company-paid lunch on office days - Growth Investment Program – funding and resources to support your personal and professional development - Tech setup – we’ll provide a company laptop and the essentials to help you get up and running smoothly Things to Know Foursquare is proud to foster an inclusive environment, free from discrimination. We believe that building the best products starts with bringing together diverse perspectives and backgrounds — it’s how we create better experiences for both our users and our team. We value every voice, and we encourage you to be part of building a company and products we love. Foursquare is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. Foursquare Privacy Policy https://location.foursquare.com/legal/privacy-center/applicant/", "summaryDescription" : "Support and Data Operations Associate (Fixed-term) at Foursquare. Skills: Data science, Data engineering, Machine learning, Business intelligence", "createdAt" : "2026-06-16T00:29:26.610", "lastUpdated" : "2026-06-16T08:56:17.647", "ingestTimestamp" : "2026-06-16T00:29:26.610", "mongoId" : "6a3055f1f292fd229cf23389", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Statistical methods", "ML frameworks", "BI platforms", "Cloud data stacks", "Modelling skills", "Regression", "Classification", "Clustering", "Time-series analysis", "A/B testing", "Causal inference", "Data science", "Data engineering", "Machine learning", "Business intelligence", "Data analytics", "Quantitative analysis", "Data modelling", "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified", "SQL", "Python", "R", "Scala", "Spark", "Dbt", "Tableau", "Power BI", "Looker", "Metabase", "Superset", "Qlik", "MicroStrategy", "Snowflake", "BigQuery", "Redshift", "Databricks", "Fivetran", "Airflow", "Dbt Cloud", "Delta Lake", "Scikit-learn", "TensorFlow", "PyTorch", "XGBoost", "LightGBM", "Hugging Face", "MLflow", "AWS", "GCP", "Azure", "S3", "Glue", "SageMaker", "Athena", "Vertex AI", "Synapse", "ML Studio" ], "skillCount" : 60, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Junior", "dataQualityScore" : 0.7777778, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "68b706997fc9a711f0f6fe81", "title" : "Senior Data Scientist - Data and Machine Learning, WWPS ProServe Data and Machine Learning", "company" : "Amazon Web Services, Inc.", "industry" : "Data Science, Science, Cloud Computing", "salary" : { "min" : 143300.0, "max" : 247600.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Herndon, Virginia, USA", "locations" : [ "Herndon, Virginia, USA" ], "timestamp" : "2026-06-15T06:03:22.811", "fingerprint" : "2de507a2af9713958cf19fc7bc76811d52243f83d9bf8296e6df9008d561a0ec", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3051327/apply", "externalId" : "17bd976f-c327-4f8f-82fd-e01156aa798f", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Herndon", "state" : "Virginia", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "38.9695316,-77.3859479" } ], "locationText" : "Herndon, Virginia, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "AI algorithms, Generative AI, Machine Learning, Large Language Models, Python, Tensorflow, Keras, PyTorch, MXNet, AWS, SageMaker, Bedrock, EC2, ECS, EKS, OpenSearch, JAX", "professionalSkills" : [ "Business acumen", "Data science", "AI methods" ], "hardSkillsList" : [ "Data mining", "Numerical optimization", "Deep learning", "Machine learning" ], "hardSkills" : [ { "name" : "Data mining", "level" : "intermediate" }, { "name" : "Numerical optimization", "level" : "intermediate" }, { "name" : "Deep learning", "level" : "intermediate" }, { "name" : "Machine learning", "level" : "intermediate" } ], "majorSkills" : "Generative AI, Machine Learning, Data Science", "majorSkillsList" : [ "Generative AI", "Machine Learning", "Data Science" ], "coreResponsibilities" : "Research AI algorithms, Design AI algorithms, Develop AI algorithms, Evaluate AI algorithms, Interact with customers, Understand business problem, Aid customers in implementation of AI solutions, Deliver briefing sessions to customers, Deliver deep dive sessions to customers, Guide customer on adoption patterns, Guide customer on paths to production, Create best practice recommendations, Deliver best practice recommendations, Create tutorials, Deliver tutorials, Create blog posts, Deliver blog posts, Create sample code, Deliver sample code, Create presentations, Deliver presentations, Provide customer feedback, Provide market feedback", "teamCollaboration" : "AI/ML scientists; Architects; Product teams; Engineering teams", "domainKnowledge" : "Generative AI; Large Language Models; US Intelligence Community", "domainList" : [ "generative-ai", "large-language-models", "us-intelligence-community" ], "domainSpecificKnowledge" : [ "Generative AI", "Large Language Models", "US Intelligence Community" ], "toolProficiency" : [ "Tensorflow", "Keras", "PyTorch", "MXNet", "JAX" ], "communicationSkills" : "Customer briefings; Deep dive sessions; Executive stakeholder presentations", "documentationSkills" : "Best practice recommendations; Tutorials; Blog posts; Sample code; Presentations", "innovationCreativity" : "Drive feature innovation", "problemSolvingSkills" : "Solve complex problems", "specialRequirements" : "TS/SCI with Polygraph, Up to 25% local travel", "qualificationsBasic" : "Bachelor's degree in Computer Science, Engineering, related field, or equivalent experience, 5+ years of experience building models for business applications, Experience with algorithms, data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing, neural deep learning methods and/or machine learning, Experience using Python, Hands on experience building models with deep learning frameworks (i. e. Tensorflow, Keras, PyTorch, MXNet), Current, active US Government Security Clearance of TS/SCI with Polygraph", "qualificationsPreferred" : "Masters or PhD Degree in computer science, engineering, mathematics, operations research, or in a highly quantitative field, AWS experience preferred, Practical experience in solving complex problems in an applied environment, Hands on experience building models with deep learning frameworks like PyTorch, Tensorflow, or JAX, Experience building applications leveraging GenAI", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Are you excited to help the US Intelligence Community design, build, and implement AI algorithms, including advanced Generative AI solutions, to augment decision making while meeting the highest standards for reliability, transparency, and scalability? The Amazon Web Services (AWS) US Federal Professional Services team works directly with US Intelligence Community agencies and other public sector entities to achieve their mission goals through the adoption of Machine Learning (ML) and Generative AI methods. We build models for text, image, video, audio, and multi-modal use cases, leveraging both traditional ML approaches and state-of-the-art generative models including Large Language Models (LLMs), text-to-image generation, and other advanced AI capabilities to fit the mission. Our team collaborates across the entire AWS organization to bring access to product and service teams, to get the right solution delivered and drive feature innovation based on customer needs. At AWS, we're hiring experienced data scientists with a background in both traditional and generative AI who can help our customers understand the opportunities their data presents, and build solutions that earn the customer trust needed for deployment to production systems. In this role, you will work closely with customers to deeply understand their data challenges and requirements, and design tailored solutions that best fit their use cases. You should have broad experience building models using all kinds of data sources, and building data-intensive applications at scale. You should possess excellent business acumen and communication skills to collaborate effectively with stakeholders, develop key business questions, and translate requirements into actionable solutions. You will provide guidance and support to other engineers, sharing industry best practices and driving innovation in the field of data science and AI. This position requires that the candidate selected must currently possess and maintain an active TS/SCI Security Clearance with Polygraph. The position further requires the candidate to opt into a commensurate clearance for each government agency for which they perform AWS work. Key job responsibilities As an Data Scientist, you will: - Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate AI algorithms to address real-world challenges - Interact with customers directly to understand the business problem, help and aid them in implementation of AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths to production. - Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder - Provide customer and market feedback to Product and Engineering teams to help define product direction - This position may require up to 25% local travel. About the team About AWS Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences and inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Basic Qualifications: - Bachelor's degree in Computer Science, Engineering, related field, or equivalent experience - 5+ years of experience building models for business applications - Experience with algorithms, data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing, neural deep learning methods and/or machine learning - Experience using Python and hands on experience building models with deep learning frameworks (i.e. Tensorflow, Keras, PyTorch, MXNet) - Current, active US Government Security Clearance of TS/SCI with Polygraph Preferred Qualifications: - Masters or PhD Degree in computer science, engineering, mathematics, operations research, or in a highly quantitative field - AWS experience preferred, with proficiency in a range of AWS services (e.g., SageMaker, Bedrock, EC2, ECS, EKS, OpenSearch) - Practical experience in solving complex problems in an applied environment - Hands on experience building models with deep learning frameworks like PyTorch, Tensorflow, or JAX - Experience building applications leveraging GenAI Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $143,300/year in our lowest geographic market up to $247,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.", "summaryDescription" : "Senior Data Scientist - Data and Machine Learning, WWPS ProServe Data and Machine Learning at Amazon Web Services, Inc.. Skills: Generative AI, Machine Learning, Data Science. Research AI algorithms. Design AI algorithms", "postedDate" : "2026-06-13T12:13:39.251", "createdAt" : "2026-06-13T12:13:39.251", "lastUpdated" : "2026-06-15T06:03:22.811", "ingestTimestamp" : "2026-06-13T12:13:39.251", "mongoId" : "68b706997fc9a711f0f6fe81", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3051327/apply", "salaryAnnualMin" : 143300, "salaryAnnualMax" : 247600, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ "Data mining", "Numerical optimization", "Deep learning", "Machine learning", "Generative AI", "Machine Learning", "Data Science", "Business acumen", "Data science", "AI methods", "Large Language Models", "US Intelligence Community", "Tensorflow", "Keras", "PyTorch", "MXNet", "JAX" ], "skillCount" : 17, "jobCategory" : "data", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true }, { "id" : "6a306a85f292fd229cfccba4", "title" : "CMT Field and Laboratory Technician", "company" : "SOCOTEC", "industry" : "Civil Engineering", "salary" : { "min" : 42000.0, "max" : 58000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for an entry-level CMT Field and Laboratory Technician in Prescott Valley, AZ, adjusted for the construction industry." }, "location" : "Prescott Valley, AZ, United States", "locations" : [ "Prescott Valley", "AZ", "United States" ], "certifications" : [ "ACI certification", "NICET certification" ], "timestamp" : "2026-06-16T11:26:19.665", "fingerprint" : "9e453530015c523007cac209a6e52845bb43b2026ff4ff045baa86670405b962", "source" : "smartrecruiters", "language" : "en", "applyUrl" : "https://jobs.smartrecruiters.com/Socotec/744000132279599-cmt-field-and-laboratory-technician", "externalId" : "744000132279599", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Prescott Valley", "state" : "Arizona", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "34.5950776,-112.3338634" } ], "locationText" : "Prescott Valley, Arizona, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 0, "experienceMaxYears" : 2, "experienceLevel" : "entry", "coreResponsibilities" : "Perform field and laboratory testing, Collect samples, Prepare samples for analysis, Conduct laboratory tests, Record and report test results, Maintain laboratory equipment, Follow safety procedures", "domainKnowledge" : "Construction materials testing; Geotechnical engineering; Concrete testing; Asphalt testing; Soil testing", "domainList" : [ "construction-materials-testing", "geotechnical-engineering", "concrete-testing", "asphalt-testing", "soil-testing" ], "domainSpecificKnowledge" : [ "Construction materials testing", "Geotechnical engineering", "Concrete testing", "Asphalt testing", "Soil testing" ], "communicationSkills" : "Report writing", "documentationSkills" : "Test reporting", "specialRequirements" : "Valid driver's license, Ability to lift 50 lbs", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "About SOCOTEC: SOCOTEC is a provider of niche consulting services within the architecture, engineering and construction industries focusing on high-performance buildings and specialty structures. Through an integrated, holistic approach, our professionals provide solutions for building envelope, energy efficiency, sustainability, code advisory and construction advisory projects. SOCOTEC offers competitive salary and benefits, mentorship, training, and social activities. SOCOTEC is proud to announce that it has been officially certified as a Great Place to Work by the renowned global authority on workplace culture, Great Place to Work®. We are seeking a Construction Materials Testing (CMT) Field & Laboratory Technician to perform field and laboratory testing of soils, concrete, asphalt, and aggregate materials in support of commercial, residential, industrial, and public works construction projects. This position offers a combination of field inspection and testing responsibilities along with laboratory testing and sample processing. Responsibilities * Perform field testing of soils, concrete, asphalt, and aggregate materials in accordance with ASTM, AASHTO, and project specifications. * Conduct soil density testing using nuclear density gauges and other field testing equipment. * Perform concrete testing including slump, air content, temperature, and casting of compressive strength cylinders. * Observe and document construction activities related to earthwork, foundations, paving, and concrete placement. * Accurately record field observations, test results, and project documentation. * Communicate testing results and project information to project managers, contractors, and clients. * Collect, transport, receive, sample, and prepare materials for laboratory testing. * Perform laboratory testing including Proctor compaction, sieve analysis, Atterberg Limits, sand equivalent, compression testing, aggregate testing, and asphalt testing. * Calculate, review, and report laboratory and field test results. * Maintain testing equipment, vehicles, and laboratory facilities in accordance with company quality and safety requirements. * Follow company safety procedures and maintain compliance with radiation safety requirements. * Assist with additional testing, inspection, and project-related duties as assigned. ## Qualifications * Experience in construction materials testing, field inspection, laboratory testing, or a related construction field preferred. * Knowledge of ASTM, AASHTO, and industry-standard testing procedures preferred. * Ability to read construction plans, specifications, and testing requirements preferred. * Strong attention to detail and ability to maintain accurate records and documentation. * Strong mathematical skills with the ability to perform calculations and verify testing data. * Ability to work independently in the field and as part of a team in a laboratory environment. * Excellent verbal and written communication skills. * Basic computer proficiency, including Microsoft Word, Excel, and electronic reporting systems. * Valid driver's license with a satisfactory driving record. * Ability to lift and carry up to 60 pounds and work outdoors in varying weather conditions. Preferred Certifications * ACI Concrete Field Testing Technician – Grade I * ATTI/WAQTC/ASTM/AASHTO Soils and Aggregate Certification * ATTI/WAQTC Asphalt Certification * Radiation Safety Certification * Nuclear Gauge Safety Certification * ACI Concrete Strength Testing Technician * Additional ICC, NICET, or construction inspection certifications are a plus Preferred Experience * Field density testing and earthwork observation * Concrete placement observation and testing * Asphalt paving observation and testing * Laboratory testing of soils, aggregates, concrete, and asphalt materials * Construction quality assurance and quality control (QA/QC) services ## Additional Information Your information will be kept confidential according to EEO guidelines. For more information, please visit www.socotec.us Job Type: Full-Time SOCOTEC is an Equal Opportunity Employer. SOCOTEC is an Equal Opportunity Employer.", "summaryDescription" : "CMT Field and Laboratory Technician at SOCOTEC. Perform field and laboratory testing. Collect samples", "postedDate" : "2026-06-15T20:12:57.000", "createdAt" : "2026-06-15T23:59:24.407", "lastUpdated" : "2026-06-16T11:26:19.665", "ingestTimestamp" : "2026-06-15T23:59:24.407", "mongoId" : "6a306a85f292fd229cfccba4", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 42000, "salaryAnnualMax" : 58000, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Construction materials testing", "Geotechnical engineering", "Concrete testing", "Asphalt testing", "Soil testing", "ACI certification", "NICET certification" ], "skillCount" : 7, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Entry", "dataQualityScore" : 1.0, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Construction", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c758574d8ee00a09373d0", "title" : "Research and Prototyping Engineer", "company" : "Arcturus", "industry" : "Internships", "salary" : { "min" : 75000.0, "max" : 95000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for an Entry-level Research and Prototyping Engineer in Los Angeles, USA, adjusted for the manufacturing industry and company size." }, "location" : "Los Angeles", "locations" : [ "Los Angeles" ], "timestamp" : "2026-06-16T00:35:02.360", "fingerprint" : "60b7b2bab613507741ba9b1d2dbe513763b0bd02e3cad4ed6c0c834d56185519", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/arcturus/f6cc56f2-38d0-4fb5-90b9-ae3650118f35/application", "externalId" : "f6cc56f2-38d0-4fb5-90b9-ae3650118f35", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Los Angeles", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "34.0536909,-118.2427660" } ], "locationText" : "Los Angeles, California, United States", "employmentType" : "FULL_TIME", "technicalSkills" : "CAD, Raman spectroscopy, Microscopy, SEM/EDS, Electrical testing, Mechanical testing", "professionalSkills" : [ "Supplier research", "Experimental tracking", "Fixture development", "Sample preparation", "Technical documentation" ], "hardSkillsList" : [ "Materials science", "Additive manufacturing", "Process engineering", "Materials characterization" ], "hardSkills" : [ { "name" : "Materials science", "level" : "intermediate" }, { "name" : "Additive manufacturing", "level" : "intermediate" }, { "name" : "Process engineering", "level" : "intermediate" }, { "name" : "Materials characterization", "level" : "intermediate" } ], "majorSkills" : "Materials science, Additive manufacturing, Process engineering, Testing", "majorSkillsList" : [ "Materials science", "Additive manufacturing", "Process engineering", "Testing" ], "coreResponsibilities" : "Support technical team across experiments, Conduct literature research, Perform supplier research, Prepare samples, Develop fixtures, Perform testing, Maintain documentation, Build and maintain supplier database, Organize recipe matrix, Support nanomaterial handling, Track experimental results, Build and maintain chamber BOMs, Track vendor quotes, Support fixture and tooling development, Organize fixture CAD library, Support additive manufacturing experiments, Support flash sintering fixture iterations, Create and improve sample preparation SOPs, Support cylinder coupon workflows, Translate experimental procedures into work instructions, Support internal materials testing, Prepare samples for external testing, Coordinate with external vendors and labs, Maintain clear technical documentation", "teamCollaboration" : "Work closely with technical leads; Work with senior engineers", "domainKnowledge" : "Carbon nanomaterials; Additive manufacturing; Electrification; Materials science; Powder processing", "domainList" : [ "carbon-nanomaterials", "additive-manufacturing", "electrification", "materials-science", "powder-processing" ], "domainSpecificKnowledge" : [ "Carbon nanomaterials", "Additive manufacturing", "Electrification", "Materials science", "Powder processing" ], "toolProficiency" : [ "Onshape" ], "documentationSkills" : "Technical documentation; Lab notes; Test summaries; Experimental results", "continuousLearning" : "Willingness to learn across multiple disciplines", "innovationCreativity" : "Prototype development", "qualificationsBasic" : "BS, MS, or PhD in materials science, mechanical engineering, chemical engineering, electrical engineering, physics, chemistry, manufacturing engineering, or a related technical field, Technical curiosity and willingness to learn, Comfortable working hands-on in a lab, shop, or experimental environment, Highly organized, detail-oriented, and reliable with documentation, Able to take direction, ask good questions, and execute quickly, Excited to work in a fast-moving startup environment", "qualificationsPreferred" : "Experience working in a research lab, hardware startup, university lab, or advanced manufacturing environment, Experience with carbon nanomaterials, graphene, carbon nanotubes, metallurgy, additive manufacturing, powder processing, or materials characterization, Familiarity with Raman spectroscopy, microscopy, SEM/EDS, electrical testing, mechanical testing, polishing, or sample preparation, CAD experience, ideally with Onshape or similar tools, Experience with literature reviews, supplier research, technical databases, or experimental documentation", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "About Arcturus Arcturus is creating a new wire technology stack that uses carbon nanomaterials to overcome the materials limitations of metals where performance breaks down, at real operating temperatures. Our technology is designed to significantly improve the performance of electric motors for drones and robotics, heat sinks, and ultimately the entire energy grid. At its core, Arcturus is developing a new class of carbon nanomaterial-infused metal matrix composites for high-performance conductor applications. Why you should join us This is a ground-floor opportunity to help build something that has never been done before. You would join as an early technical co-op and work closely with Arcturus’ technical team across nanomaterials, additive manufacturing, process engineering, and testing. This is a hands-on role for someone who wants to learn quickly, contribute directly, and help build the experimental foundation for a first-of-its-kind materials platform. Purpose We are seeking a Research and Prototyping Engineer Co-op who can support the technical team across experiments, literature research, supplier research, sample preparation, fixture development, testing, and documentation. This role is intentionally broad. You do not need to be an expert in every area, but you should be highly curious, organized, hands-on, and excited to work at the intersection of materials science, advanced manufacturing, and electrification. The role This role will work closely with Arcturus’ technical leads and senior engineers. Nanomaterials - Build and maintain a carbon nanomaterial and powder supplier database, including vendors, material specs, pricing, lead times, and sample availability - Help organize a recipe matrix for carbon nanomaterial integration, including material type, loading level, feedstock, processing route, and resulting performance - Support basic nanomaterial handling, sample preparation, documentation, and experimental tracking Additive Manufacturing - Help build and maintain chamber BOMs, equipment lists, vendor quote trackers, and component comparison tables - Support fixture and tooling development through CAD, ideally in Onshape or a similar CAD platform - Help organize a fixture CAD library for experimental setups, sample holders, coupons, and test hardware - Support additive manufacturing experiments through preparation, documentation, build tracking, and post-build sample handling Process Engineering - Support flash sintering fixture iterations, including CAD updates, part sourcing, assembly, testing, and documentation - Help create and improve sample preparation SOPs for polishing, sectioning, mounting, cleaning, labeling, and tracking - Support cylinder coupon workflows, including sample preparation, processing, inspection, measurement, and documentation - Help translate experimental procedures into clear, repeatable work instructions and lab notes Testing and Characterization - Support internal materials testing, including Raman spectroscopy, electrical characterization, mechanical characterization, polishing, microscopy, and other methods as needed - Help prepare samples and data packages for external testing, vendor evaluation, partner validation, and customer-facing demonstrations - Coordinate with external vendors and labs for quotes, sample shipments, testing status, and results tracking - Maintain clear technical documentation, including lab notes, test summaries, experimental results, and lessons learned Basic qualifications - Currently pursuing or recently completed a BS, MS, or PhD in materials science, mechanical engineering, chemical engineering, electrical engineering, physics, chemistry, manufacturing engineering, or a related technical field - Strong technical curiosity and willingness to learn across multiple disciplines - Comfortable working hands-on in a lab, shop, or experimental environment - Highly organized, detail-oriented, and reliable with documentation - Able to take direction, ask good questions, and execute quickly - Excited to work in a fast-moving startup environment where priorities can change quickly Preferred qualifications - Experience working in a research lab, hardware startup, university lab, or advanced manufacturing environment - Experience with carbon nanomaterials, graphene, carbon nanotubes, metallurgy, additive manufacturing, powder processing, or materials characterization - Familiarity with Raman spectroscopy, microscopy, SEM/EDS, electrical testing, mechanical testing, polishing, or sample preparation - CAD experience, ideally with Onshape or similar tools - Experience with literature reviews, supplier research, technical databases, or experimental documentation What we offer - Hands-on technical experience with first-of-its-kind materials and manufacturing challenges - The chance to work closely with senior technical leads across nanomaterials, additive manufacturing, process engineering, and testing - Real ownership over useful technical projects, databases, fixtures, experiments, and documentation - Up to a one-year co-op experience with direct exposure to early-stage deeptech startup building. If the fit is right, we'd love to bring you on to the team! If this role excites you, even if you do not check every box, we’d love to hear from you. We’d rather work with a fast learner who cares deeply about the work than someone with years of experience but little curiosity.", "summaryDescription" : "Research and Prototyping Engineer at Arcturus. Skills: Materials science, Additive manufacturing, Process engineering, Testing. Support technical team across experiments. Conduct literature research", "createdAt" : "2026-06-14T20:11:35.092", "lastUpdated" : "2026-06-16T00:35:02.360", "ingestTimestamp" : "2026-06-14T20:11:35.092", "mongoId" : "6a2c758574d8ee00a09373d0", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 75000, "salaryAnnualMax" : 95000, "salaryBand" : "75k-100k", "hasSalary" : true, "allSkills" : [ "Materials science", "Additive manufacturing", "Process engineering", "Materials characterization", "Testing", "Supplier research", "Experimental tracking", "Fixture development", "Sample preparation", "Technical documentation", "Carbon nanomaterials", "Electrification", "Powder processing", "Onshape" ], "skillCount" : 14, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Entry", "dataQualityScore" : 0.7777778, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Manufacturing", "llmIndustryConfidence" : 0.95 }, { "id" : "6a307f62f292fd229c058aac", "title" : "Director of Research and Engineering, Health and Home", "industry" : "Healthcare", "salary" : { "min" : 250000.0, "max" : 350000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Director of Research and Engineering in Mountain View, CA, adjusted for the healthcare industry and director-level seniority." }, "location" : "[Mountain View, CA, USA, [100 Bay Vw Dr, Mountain View, CA 94043, USA], Mountain View, 94043, CA, US]", "locations" : [ "[Mountain View, CA, USA, [100 Bay Vw Dr, Mountain View, CA 94043, USA], Mountain View, 94043, CA, US]" ], "timestamp" : "2026-06-16T14:40:16.845", "fingerprint" : "2dcff30a13f8a7f568f69f39dde631d8ef18daa225cada80b6537ea1cb693bc4", "source" : "google", "language" : "en", "externalId" : "112964911318868678", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Mountain View", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", 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Centre Canada ULC", "industry" : "Data Science, Data Engineering, north america stores", "salary" : { "min" : 103300.0, "max" : 172600.0, "currency" : "CAD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Vancouver, British Columbia, CAN", "locations" : [ "Vancouver, British Columbia, CAN" ], "timestamp" : "2026-06-15T03:12:51.771", "fingerprint" : "be379a15adb0d165f4e7fbac44c1dc26058391c402487f29249070d19d908bff", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.jobs/jobs/10438823/apply", "externalId" : "88a730ec-f4bb-4fe3-bfe8-4633080161a6", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Vancouver", "state" : "British Columbia", "country" : "Canada", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "49.2608724,-123.1139520" } ], "locationText" : "Vancouver, British Columbia, Canada", "employmentType" : "FULL_TIME", "experienceMinYears" : 3, "experienceMaxYears" : 5, "experienceLevel" : "Mid", "technicalSkills" : "AWS, Redshift, S3, Glue, EMR, Kinesis, Lambda, Python, Scala, Airflow", "professionalSkills" : [ "Data modeling", "Data warehousing", "ETL pipelines", "Infrastructure-as-code", "CI/CD" ], "hardSkillsList" : [ "Data processing systems", "Data pipeline performance", "Data reliability", "Cost-efficiency" ], "softSkillsList" : [ "Mentoring" ], "hardSkills" : [ { "name" : "Data processing systems", "level" : "intermediate" }, { "name" : "Data pipeline performance", "level" : "intermediate" }, { "name" : "Data reliability", "level" : "intermediate" }, { "name" : "Cost-efficiency", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Mentoring" } ], "majorSkills" : "Data engineering, AWS services, Data pipelines", "majorSkillsList" : [ "Data engineering", "AWS services", "Data pipelines" ], "coreResponsibilities" : "Design data processing systems, Build data processing systems, Operate data processing systems, Leverage expertise in Python, Develop custom data processing frameworks, Develop automation tools, Collaborate with data scientists, Collaborate with analysts, Collaborate with product managers, Optimize data pipeline performance, Optimize data pipeline reliability, Optimize data pipeline cost-efficiency, Mentor junior engineers, Share knowledge of data engineering, Stay up-to-date with big data technologies, Stay up-to-date with architectural patterns, Drive adoption of innovative solutions", "teamCollaboration" : "With data scientists; With analysts; With product managers", "domainKnowledge" : "Promotions data; Promotional strategies; Selling Partners; Big data technologies; Architectural patterns", "domainList" : [ "promotions-data", "promotional-strategies", "selling-partners", "big-data-technologies", "architectural-patterns" ], "domainSpecificKnowledge" : [ "Promotions data", "Promotional strategies", "Selling Partners", "Big data technologies", "Architectural patterns" ], "toolProficiency" : [ "Airflow", "Redshift", "S3", "Glue", "EMR", "Kinesis", "Lambda" ], "continuousLearning" : "Stay up-to-date with technologies; Drive adoption of solutions", "innovationCreativity" : "Drive adoption of innovative solutions", "problemSolvingSkills" : "Translate business requirements", "qualificationsBasic" : "3+ years of data engineering experience, Experience with data modeling, Experience with warehousing, Experience building ETL pipelines", "qualificationsPreferred" : "Experience with AWS technologies, Experience with non-relational databases, Usage of generative AI tools, Willingness to learn AI prompting, Ability to recognize AI opportunities", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Are you passionate about developing the next generation of data infrastructure capable of handling complex, mission-critical data pipelines and analytics workloads? Do you want to build next generation data engineering solutions that leverage the latest AWS technologies to process a broad range of business and customer data? Join our WW Promotions Data and Insights team, where you'll have the opportunity to continuously improve the systems that enable Amazon's promotional strategies across every major shopping event worldwide. Key job responsibilities 1. Design, build, and operate highly scalable, fault-tolerant data processing systems using modern AWS services like Redshift, S3, Glue, EMR, Kinesis, and Lambda, and orchestration systems using Airflow 2. Leverage your expertise in Python, Scala, or other modern programming languages to develop custom data processing frameworks and automation tools 3. Collaborate closely with data scientists, analysts, and product managers to understand business requirements and translate them into technical solutions 4. Continuously optimize data pipeline performance, reliability, and cost-efficiency using best practices in CI/CD and infrastructure-as-code 5. Mentor junior engineers and share your knowledge of data engineering best practices 6. Stay up-to-date with the latest big data technologies and architectural patterns, and drive the adoption of innovative solutions About the team Promotions reinforce a positive perception of Amazon’s price leadership with shoppers by complementing our everyday great prices with time-bound discounts on a broad selection of high-quality products. For Selling Partners (SPs), promotions create incremental demand for their products and increase their share of voice, clear inventory, and drive traffic to new selection. WW Promotions owns the sourcing and execution of promotions at Amazon and we are their data & analytics team. We serve as the central stewards of promotions data, delivering trusted and governed datasets that power product development, machine learning models, and business analytics across the organization. Basic Qualifications: - 3+ years of data engineering experience - Experience with data modeling, warehousing and building ETL pipelines Preferred Qualifications: - Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions - Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases) - Usage of generative AI tools to enhance workflow efficiency, with a willingness to learn effective prompting and evaluation practices. - Ability to recognize opportunities where generative AI could enhance products, workflows, or customer experiences. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. As a total compensation company, Amazon's package may include other elements such as sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon offers comprehensive benefits including health insurance (medical, dental, vision, prescription, basic life & AD&D insurance), Registered Retirement Savings Plan (RRSP), Deferred Profit Sharing Plan (DPSP), paid time off, and other resources to improve health and well-being. We thank all applicants for their interest, however only those interviewed will be advised as to hiring status. CAN, BC, Vancouver - 103,300.00 - 172,600.00 CAD annually", "summaryDescription" : "Data Engineer, WW Promotions Data and Insights at Amazon Development Centre Canada ULC. Skills: Data engineering, AWS services, Data pipelines. Design data processing systems. Build data processing systems", "postedDate" : "2026-06-13T09:12:42.868", "createdAt" : "2026-06-13T09:12:42.868", "lastUpdated" : "2026-06-15T03:12:51.771", "ingestTimestamp" : "2026-06-13T09:12:42.868", "mongoId" : "6a2176c774d8ee00a0c1adbc", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.jobs/jobs/10438823/apply", "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ "Data processing systems", "Data pipeline performance", "Data reliability", "Cost-efficiency", "Mentoring", "Data engineering", "AWS services", "Data pipelines", "Data modeling", "Data warehousing", "ETL pipelines", "Infrastructure-as-code", "CI/CD", "Promotions data", "Promotional strategies", "Selling Partners", "Big data technologies", "Architectural patterns", "Airflow", "Redshift", "S3", "Glue", "EMR", "Kinesis", "Lambda" ], "skillCount" : 25, "jobCategory" : "data", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true }, { "id" : "6a307f2df292fd229c055eac", "title" : "Staff Data Scientist, Discover Personalization and Quality", "industry" : "Technology", "salary" : { "min" : 225000.0, "max" : 350000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Lead Staff Data Scientist in Mountain View, CA, adjusted for the technology industry and a large company size." }, "location" : "[Mountain View, CA, USA, [100 Bay Vw Dr, Mountain View, CA 94043, USA], Mountain View, 94043, CA, US]", "locations" : [ "[Mountain View, CA, USA, [100 Bay Vw Dr, Mountain View, CA 94043, USA], Mountain View, 94043, CA, US]", "[New York, NY, USA, [New York, NY, USA], New York, null, NY, US]" ], "certifications" : [ "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified" ], "timestamp" : "2026-06-16T10:46:29.512", "fingerprint" : "1b753ce697dfd232a32fa54cf67500ba9977d28e7d9b8f4f918c6432c0ce4afb", "source" : "google", "language" : "en", "externalId" : "92402841288614598", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Mountain View", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "37.3893889,-122.0832101" } ], "locationText" : "Mountain View, California, United States", "technicalSkills" : "Python, SQL, R, Scala, Spark, Dbt, Snowflake, BigQuery, Redshift, Databricks, Fivetran, Airflow, Dbt Cloud, Delta Lake, AWS, S3, Glue, SageMaker, Athena, GCP, Vertex AI, Azure, Synapse, ML Studio, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow", "professionalSkills" : [ "Data modeling", "Statistical analysis", "Machine learning", "Experiment design", "Causal inference" ], "hardSkillsList" : [ "Data science", "Machine learning", "Statistical modeling", "Experimentation", "Causal inference" ], "hardSkills" : [ { "name" : "Data science", "level" : "intermediate" }, { "name" : "Machine learning", "level" : "intermediate" }, { "name" : "Statistical modeling", "level" : "intermediate" }, { "name" : "Experimentation", "level" : "intermediate" }, { "name" : "Causal inference", "level" : "intermediate" } ], "majorSkills" : "Machine learning, Data science, Personalization, Quality", "majorSkillsList" : [ "Machine learning", "Data science", "Personalization", "Quality" ], "coreResponsibilities" : "Develop and deploy machine learning models, Design and implement experiments, Analyze data to identify trends, Build and maintain data pipelines, Collaborate with engineering teams, Communicate findings to stakeholders, Mentor junior data scientists", "teamCollaboration" : "Cross-functional teams; 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The Consultant will work with diverse clients ranging from small and medium size enterprises to Fortune 100 firms. Working in a t", "summaryDescription" : "Consultant - Data Visualization and User Experience at Pyrovio. Skills: data visualization, user interface, user experience, data storytelling. 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AWS account teams; Solution architects; Specialist teams", "projectManagementSkills" : [ "Roadmap development" ], "domainKnowledge" : "Manufacturing; Semiconductor industry; Data platforms; Analytics solutions; AI/ML workloads; Data lakes; Data mesh; Lakehouses; Streaming analytics; Enterprise data warehouses; Industry 4.0; Smart Manufacturing; IoT; Digital twin; Edge-to-cloud architectures; OT/IT convergence; Generative AI architectures; RAG patterns; Foundation model fine-tuning; AI agents", "domainList" : [ "manufacturing", "semiconductor-industry", "data-platforms", "analytics-solutions", "ai-ml-workloads", "data-lakes", "data-mesh", "lakehouses", "streaming-analytics", "enterprise-data-warehouses", "industry-4-0", "smart-manufacturing", "iot", "digital-twin", "edge-to-cloud-architectures", "ot-it-convergence", "generative-ai-architectures", "rag-patterns", "foundation-model-fine-tuning", "ai-agents" ], "domainSpecificKnowledge" : [ "Manufacturing", "Semiconductor industry", "Data platforms", "Analytics solutions", "AI/ML workloads", "Data lakes", "Data mesh", "Lakehouses", "Streaming analytics", "Enterprise data warehouses", "Industry 4.0", "Smart Manufacturing", "IoT", "Digital twin", "Edge-to-cloud architectures", "OT/IT convergence", "Generative AI architectures", "RAG patterns", "Foundation model fine-tuning", "AI agents" ], "toolProficiency" : [ "Amazon S3", "AWS Glue", "Amazon Redshift", "Amazon EMR", "Amazon Kinesis", "AWS Lake Formation", "Amazon SageMaker", "Amazon Bedrock" ], "communicationSkills" : "Technical concepts; Customer presentations", "documentationSkills" : "Whitepapers; Blog posts; Reference architectures", "continuousLearning" : "Emerging AWS services; Industry trends", "problemSolvingSkills" : "Root cause analysis", "outcomesObjectives" : "Unlock business value from data assets; Accelerate cloud adoption journey", "qualificationsBasic" : "Experience conveying complex technical concepts, Bachelor's degree or above in computer science, computer engineering, or related field, Bachelor's degree and 1+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience, 8+ years of experience in data engineering, data architecture, or cloud architecture, 5+ years hands-on designing and implementing data solutions on AWS or other major cloud platforms, Deep expertise in data platform technologies, Proficiency in Python, SQL, Spark, or Scala, Fluency in Mandarin Chinese and English", "qualificationsPreferred" : "Experience with large scale IT/digital business transformation or migration programs, Domain expertise in manufacturing and/or semiconductor industries, Experience with Industry 4.0 / Smart Manufacturing initiatives, Experience with generative AI architectures, Familiarity with data privacy and compliance requirements in the Taiwan market", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "We are seeking an experienced Data and AI Cloud Architect to join our AWS Professional Services team in Taiwan. In this role, you will work directly with enterprise customers — particularly in the manufacturing and semiconductor industries — to design and implement modern data platforms, analytics solutions, and AI/ML workloads on AWS. You will serve as a trusted technical advisor, helping customers accelerate their cloud adoption journey and unlock business value from their data assets. Key job responsibilities Key Responsibilities - Lead the architecture design and delivery of data and AI solutions on AWS for strategic customers in Taiwan, with a focus on manufacturing and semiconductor verticals - Design end-to-end data architectures including data lakes, data mesh, lakehouses, streaming analytics, and enterprise data warehouses using AWS services (e.g., Amazon S3, AWS Glue, Amazon Redshift, Amazon EMR, Amazon Kinesis, AWS Lake Formation) - Architect and implement AI/ML solutions leveraging Amazon SageMaker, Amazon Bedrock, and other AWS AI services to address industry-specific use cases (predictive maintenance, yield optimization, defect detection, supply chain optimization) - Collaborate with customers' technical and business stakeholders to define data strategies, roadmaps, and governance frameworks - Lead technical workstreams within ProServe engagements, mentoring junior architects and consultants - Develop reusable assets, frameworks, and best practices for Data & AI solution delivery within the manufacturing and semiconductor domains - Partner with AWS account teams, solution architects, and specialist teams to identify and shape new customer opportunities - Contribute to thought leadership through whitepapers, blog posts, reference architectures, and customer presentations - Stay current with emerging AWS services and industry trends in data engineering, analytics, and generative AI About the team AWS Professional Services works with enterprise customers and partners to help them realize their desired business outcomes through cloud adoption. Our team assists customers in achieving the greatest value from AWS by providing guidance, best practices, and hands-on delivery support throughout their cloud journey. Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Inclusive Team Culture AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. Mentorship and Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Basic Qualifications: - Experience conveying complex technical concepts to both technical and business audiences - Bachelor's degree or above in computer science, computer engineering, or related field, or Bachelor's degree and 1+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience - 8+ years of experience in data engineering, data architecture, or cloud architecture, with 5+ years hands-on designing and implementing data solutions on AWS or other major cloud platforms - Deep expertise in data platform technologies: data lakes, data warehouses, ETL/ELT pipelines, streaming architectures, and data governance, with proficiency in Python, SQL, Spark, or Scala - Fluency in Mandarin Chinese and English (written and verbal) Preferred Qualifications: - Experience with large scale IT/digital/business transformation or migration programs in a customer facing role - Domain expertise in manufacturing and/or semiconductor industries — understanding of fab operations, MES/ERP integration, equipment health monitoring, yield management, process control (SPC/FDC), supply chain digitization, and semiconductor-specific data challenges (high-volume time-series data, wafer-level analytics, APC, predictive maintenance) - Experience with Industry 4.0 / Smart Manufacturing initiatives including IoT, digital twin, edge-to-cloud architectures, and OT/IT convergence for industrial data integration - Experience with generative AI architectures including RAG patterns, foundation model fine-tuning, and AI agents - Familiarity with data privacy and compliance requirements in the Taiwan market Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.", "summaryDescription" : "Data and AI Architect, Professional Services - Taiwan at Amazon Web Services Taiwan Limited. Skills: Data Architecture, AI/ML, AWS. Lead architecture design and delivery of data and. 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Calculate retention, Apply confidence intervals, Perform significance testing, Use AI for analysis, Write SQL with LLMs, Draft frameworks with LLMs, Structure analysis with LLMs", "teamCollaboration" : "Embedded in product teams; Work with engineering; Collaborate with product; Work with design; Collaborate with product marketing; Hold ground respectfully", "projectManagementSkills" : [ "Roadmap decisions" ], "domainKnowledge" : "Banking infrastructure; Payments; Fintech; Attach rate; Payment rails; KYC; AP workflows; Pre-authorized payments; Balance/deposit metrics; Churn dynamics", "domainList" : [ "banking-infrastructure", "payments", "fintech", "attach-rate", "payment-rails", "kyc", "ap-workflows", "pre-authorized-payments", "balance-deposit-metrics", "churn-dynamics" ], "domainSpecificKnowledge" : [ "Banking infrastructure", "Payments", "Fintech", "Attach rate", "Payment rails", "KYC", "AP workflows", "Pre-authorized payments", "Balance/deposit metrics", "Churn dynamics" ], "toolProficiency" : [ "Metabase", "Looker", "Tableau", "Sigma", "Snowflake", "Dbt Cloud" ], "communicationSkills" : "Translate roadmap decisions; Present findings; Respectful disagreement", "problemSolvingSkills" : "Debug ambiguous numbers; Root cause analysis", "qualificationsBasic" : "2-4+ years product analytics, SQL proficiency, Dbt-comfortable, Metabase, Looker, Tableau, Sigma experience", "qualificationsPreferred" : "PhD preferred, Fintech familiarity, GCP Professional Data Engineer, AWS Data Analytics, Databricks Certified, Dbt Certified", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "ABOUT FLOAT Float is on a mission to simplify finance for Canadian businesses, empowering them to eliminate complexity and unlock new opportunities. Through our innovative platform, Float enables businesses to streamline financial operations and optimize cash flow, so they can focus on what matters most: growth. As one of Canada’s fastest growing companies https://www.theglobeandmail.com/business/rob-magazine/top-growing-companies/article-ranking-canadas-top-growing-companies-of-2024/ and top-rated startups in 2025 https://www.linkedin.com/posts/floatfinancial_were-proud-to-share-that-float-has-been-activity-7387093684720300032-2DDz/, 2024 https://www.linkedin.com/pulse/linkedin-top-startups-2024-15-canadian-companies-rise-linkedin-news-llihe/ and 2023 https://lnkd.in/TSU23CA, Float is customer-obsessed, passionate and entrepreneurial, with a team that includes leaders from Uber, Stripe, Shopify, Top Hat, Ada, Doordash, Snowflake, and Wealthsimple. At Float, everyone is an owner, bringing their unique perspective to our team and product. Your voice is important, and we take having a culture based on feedback seriously. We openly share our thoughts and differing opinions so we can continue to improve. We do our best to keep our decision-making decentralized so that all team members feel ownership in our success. OUR PRODUCT Float is Canada's complete business finance platform, combining modern financial services and software to help businesses spend, save, and grow. Trusted by 6000+ Canadian companies, Float provides high-limit corporate cards, automated expense management, next-day bill payments, high-yield accounts and fast, friendly support—all built in Canada, for Canada. Float is backed by world-class venture and fintech investors, including Growth Equity at Goldman Sachs Alternatives and OMERS Ventures, partners behind our $70 million Series B raise https://floatfinancial.com/we-raised-70-million-to-fix-canadas-business-banking-problem/. Our team is a collection of ambitious, collaborative and mission-driven people from all walks of life but with one goal: helping Canadian companies not just survive but thrive. And we’re looking for bold innovators to help shape the future of business finance in Canada. AI USE IN OUR HIRING PROCESS We use technology, including artificial intelligence (AI), to support parts of our hiring process. This may include AI-assisted scheduling and candidate communications, and AI-generated interview notes, guides or summaries to help our team focus on the conversation. All hiring decisions are made by our hiring team. ABOUT THE ROLE Float is building the financial operating system for Canadian businesses — corporate cards, business bank accounts, bill payments, all in one place. Reporting to the Head of Data, this role is embedded inside the product teams behind two of those core pillars: banking infrastructure and payments. Both are high-complexity, high-stakes areas that generate a dense mix of financial, behavioral, and operational data. This role owns that data layer. You're building cohorts before anyone asks, designing measurement frameworks before features go to engineering, and debugging numbers to the source — pipeline issue, definition mismatch, or real product signal. You're also someone who uses AI to move faster without losing rigour. Getting useful outputs from a model means knowing the business and data well enough to give it the right context — that's part of the job too. WHAT YOU'LL BE DOING - Define what needs to be measured before features ship and support the instrumentation to measure it. You translate roadmap decisions into measurement requirements. - Design and get broad alignment on measurement frameworks before features go to engineering — hypothesis, cohorts, success criteria. - Design and analyze experiments - structure A/B tests for product changes. Define the hypothesis, select the right unit of randomization, size the experiment for sufficient power and interpret results with statistical rigour - Own the metrics and dashboards for Banking and Payments. Every number is traceable to a reliable dbt model. You keep them accurate. - Own data quality in your product area — audit dbt models, write clear briefs for analytics engineering, flag gaps before they become problems. - Run cohort and retention analysis natively — activation sequences, behavioral funnels, leading vs. lagging indicators. Diagnose which lever moves the number, not just what happened. - Debug ambiguous numbers to the source — pipeline issue, definition mismatch, or real product signal. You close the loop. - Write expert SQL and bring statistical rigour — cohort construction, retention calculations, confidence intervals, significance testing. You know when you have enough signal to act. - Use AI as a multiplier — accelerate analysis, generate first-pass SQL, and pressure-test hypotheses faster than you could alone. You know how to give a model the business and data context that makes its outputs impactful. - Take your share of ad-hoc requests on rotation — owning your product area gives the broader data team meaningful breathing room. WHAT SUCCESS LOOKS LIKE - Get Embedded: Both team leads treat you as the owner of their data layer. KPI definitions are agreed upon, documented, and tied to reliable dbt models. Gaps are flagged with a fix in motion. - Build the Measurement Layer: Features ship with measurement frameworks designed upfront. Dashboards for the core banking and payments metrics are clean, trusted, and traceable. - Drive Product Evidence: Product decisions are shaped by your analysis before they are made. When a team lead is asked by leadership whether a feature is landing, they already know — because you’ve built the infrastructure that makes the question answerable. WHAT WE'RE LOOKING FOR - Product analytics depth — you've been embedded in a product team, own activation funnels and cohort retention natively, and know how to instrument a feature before it ships. - Experimentation and measurement design — you design A/B tests and quasi-experiments from the ground up: hypothesis, randomization unit, sample size and power calculations, guardrail metrics, and holdout design. You build pre/post and diff-in-diff analyses where randomization isn't feasible, and you know how to communicate the difference in confidence between the two - Data layer ownership — you're the DRI for data quality in your product area: auditing dbt models, writing briefs for analytics engineering, and debugging ambiguous numbers to the source. - Expert-level SQL — you build complex multi-step queries across large behavioral datasets, optimize for performance, and explain the logic to non-technical stakeholders. - Statistical reasoning — you understand distributions, confidence intervals, significance testing, and sample size constraints. You design for confounders, know when you have enough signal, and communicate uncertainty in plain language. - Data modeling literacy — you translate business logic into data requirements, specify the grain a table needs, and have informed opinions on how metrics get structured in dbt. - Comfort with imperfect data — you make a reasoned call, state your confidence level, and give stakeholders something actionable rather than waiting for clean infrastructure. - Stakeholder fluency — you work effectively across Product, Design, Engineering, and Product Marketing, and hold your ground respectfully when data contradicts what the team wants to believe. - AI as an accelerator — you've used LLMs to write SQL, draft frameworks, or structure analysis, and you know where they're reliable and where they need guardrails. - 2–4+ years in product analytics, ideally embedded in a product team at a high-growth fintech or SaaS company. - BI tool experience — Metabase, Looker, Tableau, Sigma, or similar. - dbt-comfortable (reading models, understanding lineage) with Snowflake or a comparable cloud warehouse. - Fintech familiarity — attach rate, payment rails, KYC, AP workflows, pre-authorized payments, balance/deposit metrics, churn dynamics — is a meaningful differentiator. OUR HIRING PHILOSOPHY We hire for character, curiosity, and learning velocity before credentials. Titles matter less than impact, and every hire is expected to raise the bar for Float as a whole. WHY YOU SHOULD JOIN - Work at one of Canada's fastest-growing fintech companies - Make a real impact in a high-autonomy, high-growth role - Collaborate with an ambitious and supportive team - Competitive compensation, equity options, and benefits - Hybrid work model – we are based in Toronto with in-office days for connection and collaboration - Enjoy catered team lunches every Tuesday, Wednesday and Thursday - Bring your pup to our dog-friendly office - Thrive in a high-trust, high-performance culture where your work truly matters IN SHORT At Float, you’ll thrive if you’re bold, curious, and eager to make a real impact. We're building something special—and having a lot of fun along the way. If you’re excited to build, grow, and win together, we’d love to meet you. We’re committed to building a workplace that’s welcoming and accessible for everyone. If you need any accommodations during the hiring process or once you join Float, just let us know! You can reach out to Vic https://www.linkedin.com/in/victoria-boult-b21b2053/ (victoria@floatfinancial.com), and we’ll work with you to make sure you have what you need to succeed.", "summaryDescription" : "Data Analyst, Product (Banking and Payments) at Float. Skills: Product analytics, Data engineering, Machine learning, Business intelligence. Define measurement requirements. 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More than 200,000 developers and 1,300+ organizations build voice offerings that are ‘Powered by Deepgram’, including Twilio, Cloudflare, Sierra, Decagon, Vapi, Daily, Cresta, Granola, and Jack in the Box. Deepgram’s voice-native foundation models are accessed through cloud APIs or as self-hosted and on-premises software, with unmatched accuracy, low latency, and cost efficiency. Backed by a recent Series C led by leading global investors and strategic partners, Deepgram has processed over 50,000 years of audio and transcribed more than 1 trillion words. There is no organization in the world that understands voice better than Deepgram. COMPANY OPERATING RHYTHM At Deepgram, we expect an AI-first mindset—AI use and comfort aren’t optional, they’re core to how we operate, innovate, and measure performance. Every team member who works at Deepgram is expected to actively use and experiment with advanced AI tools, and even build your own into your everyday work. We measure how effectively AI is applied to deliver results, and consistent, creative use of the latest AI capabilities is key to success here. Candidates should be comfortable adopting new models and modes quickly, integrating AI into their workflows, and continuously pushing the boundaries of what these technologies can do. Additionally, we move at the pace of AI. Change is rapid, and you can expect your day-to-day work to evolve just as quickly. This may not be the right role if you’re not excited to experiment, adapt, think on your feet, and learn constantly, or if you’re seeking something highly prescriptive with a traditional 9-to-5. OPPORTUNITY We're looking for an exceptional lawyer to join our lean, high-impact legal team and lead legal work across our models and the products built on them. This role is for someone who thrives at the intersection of law and model development — a builder with sharp instincts and sound judgment who is steady under ambiguity and fluent in product. Our legal team has a real seat at the table. You'll partner with our research and data teams on the novel legal questions inside model development, and advise our product teams on the experiences we put in front of users. You'll help Deepgram move at the speed of an ambitious voice AI company while keeping pace with the AI legal frameworks coming online internationally. Many of the questions in our space don't have settled answers yet. That's the best part of the job. You'll think them through from first principles, design the frameworks that let us scale, and help Deepgram continue to earn its place as the trusted leader in voice AI. This role is ideal for someone with genuine conviction that voice is the most consequential interface with AI, and who wants to spend the next phase of their career on the legal questions that will define it. You'll be the third lawyer on our team, reporting directly to our General Counsel and helping establish a legal function that scales with a company on a steep trajectory, using AI as your default mode of working to set the standard for what AI-native legal work looks like. What You’ll Do - Be the go-to counsel for our data and research teams on the legal questions inside model development, and design the frameworks that let research move fast with confidence - Partner with our product teams to ship products and features that delight our users. - Draft and review the consumer-facing terms, policies, disclosures, and marketing that go with our products — written for customers, not lawyers - Continue building out our privacy program — and tell its story to customers — to deepen customer trust in our products - Stay ahead of the AI legal frameworks developing internationally, translate developments into principles and policies our teams can act on, and help Deepgram develop a clear point of view on responsible AI development - Develop deep expertise across the legal questions defining AI today, and help advance how our company, and the broader field, thinks about them - Build the AI-native legal function at Deepgram with workflows and systems that scale our team’s impact You'll Love This Role If You - Are passionate about AI and the ability to work alongside cutting-edge researchers and engineering teams - Get energized by being the first — building systems from scratch, establishing foundational practices, and turning novel legal questions into ones with answers - Are very practical in addressing legal issues and allergic to unnecessary friction - Have an abiding spirit of idealism about your chosen profession — you're not just answering legal questions, you're building something that matters - Have a point of view on what good lawyering looks like and a healthy sense of humor about everything else It's Important To Us That You Have - JD from a U.S. accredited law school and 7–15 years of experience in legal practice (or more), in-house, at a firm, or both - Demonstrated experience counseling product, research, or engineering teams on the legal questions that come up in how AI gets built and deployed - Fluency in the issues that matter most to us: privacy, IP, data licensing, consumer protection, and the international AI regulatory landscape. Depth in some, excited to learn the rest - Recognize that law is about the grey areas, and are comfortable living in them, while giving clear and actionable advice - An AI-native legal practice — workflows you've built into your own work, not just tools you've used - Exceptional writing — precise, plain, and compelling It Would Be Great If You Had - Hands-on experience at a foundation model company or AI research lab — you've seen how legal questions actually arise inside model development - Depth in one or more emerging AI regulatory regimes (EU AI Act, US states, UK, APAC) We read cover letters! If you want to stand out: Tell us about a novel legal question you worked through without a playbook — how you reasoned through it and where you landed. BENEFITS & PERKS* HOLISTIC HEALTH - Medical, dental, vision benefits - Annual wellness stipend - Mental health support - Life, STD, LTD Income Insurance Plans WORK/LIFE BLEND - Unlimited PTO - Parental leave - Flexible schedule - 12 Paid US company holidays - Quarterly personal productivity stipend - One-time stipend for home office upgrades - 401(k) plan with company match - Tax Savings Programs CONTINUOUS LEARNING - Learning / Education stipend - Participation in talks and conferences - Employee Resource Groups - AI enablement workshops / sessions *For candidates outside of the US, we use an Employer of Record model in many countries, which means benefits are administered locally and governed by country-specific regulations. Because of this, benefits will differ by region — in some cases international employees receive benefits US employees do not, and vice versa. As we scale, we will continue to evaluate where we can create more alignment, but a 1:1 global benefits structure is not always legally or operationally possible. Backed by prominent investors including Y Combinator, Madrona, Tiger Global, Wing VC and NVIDIA, Deepgram has raised over $215M in total funding. If you're looking to work on cutting-edge technology and make a significant impact in the AI industry, we'd love to hear from you! Deepgram is an equal opportunity employer. We want all voices and perspectives represented in our workforce. We are a curious bunch focused on collaboration and doing the right thing. We put our customers first, grow together and move quickly. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, gender identity or expression, age, marital status, veteran status, disability status, pregnancy, parental status, genetic information, political affiliation, or any other status protected by the laws or regulations in the locations where we operate. We are happy to provide accommodations for applicants who need them.", "summaryDescription" : "Associate General Counsel (Product and Research) at Deepgram. Skills: Legal compliance, Product law, Research law. Provide legal counsel. 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Skills: Machine Learning, Data Science, Statistical Modeling. Conduct research and develop novel ML models. 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Our experts in public health, performance evaluation, and health operations solve the complex problems faced by civilian and military customers alike by leveraging advanced tools – including digital transformation, artificial intelligence, data analytics, cloud enablement, modeling, and simulation, and more. With over 2,400 employees dedicated to the idea that “Your Mission is Our Passion,” DLH brings a unique combination of government sector experience, proven methodology, and unwavering commitment to innovation to improve the lives of millions. Overview DLH Corp, is looking for a Public Health Research Analyst (Non-Data) to join our talented and innovative team supporting the Centers for Disease Control and Prevention (CDC). CDC’s National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention (NCHHSTP), the Division of HIV Prevention (DHP) is charged with preventing HIV infection and reducing the incidence of HIV-related illness and death. The overarching objectives of the contract held by DLH are to assist DHP in addressing its public health mission by providing data management, data governance, data analysis, and data dissemination support to strengthen the nationwide capacity to monitor the HIV epidemic. This position is 100% remote. However, employees may be required to attend occasional in-person meetings, trainings, or team events on an as-needed basis. To support onboarding and compliance requirements, candidates must reside within reasonable commuting distance of Atlanta, GA; Chicago, IL; or Washington, DC. Access to one of these secure office locations is required for smart card issuance, background investigation processing, and other periodic administrative or security-related activities. Responsibilities Ensure the capture of program data. Produce reports based on program data. Monitor the commitment and obligation of funds. Prepare reports on disbursement of funded research or demonstration projects. Help translate scientific evidence from the literature into practical information. Support ongoing coordination and management of program activity. Qualifications Bachelor’s degree in public health or related field. Demonstrated ability to work with multiple data sources to monitor and assess data to ensure data quality, including accuracy and completeness. At least 2 years of experience with managing or running a research or demonstration project. Familiarity with public health research budgets and expenditures. Excellent written and verbal communication skills. Ability to multitask and prioritize competing needs. Must be able to obtain a NAC clearance Preferred Qualifications Experience handling public health research projects. Experience with systematic reviews. Prior experience with CDC, HHS, or other federal or state health agency. Master’s degree in public health or related field. Detail oriented and able to create meticulous documentation of products. Strong organizational and interpersonal skills. Basic Compensation: $50,000 - $70,000 yearly salary The salary range listed reflects what we reasonably expect to pay for this role at the time of posting. The final offer may vary based on skills, experience, geographic location, market conditions, and internal equity. Additional compensation may include performance incentives and program-specific awards. We do not use salary history to determine compensation, in line with applicable law. Benefits DLH Corp offers our employees an excellent benefits package, including Personal Time Off (PTO), medical, dental, vision, supplemental life with AD therefore, we offer a 401(k) Retirement Plan, which includes a matching component. DLH is dedicated to your career development, providing training to help drive success, with access to our best-in-class e-learning suite for formal and informal learning, professional and technical certification preparation, and education assistance at accredited institutions. #LI-REMOTE EEO DLH Corporation is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment. DLH will provide reasonable accommodation to individuals with disabilities and disabled Veterans who need assistance to apply. DLH is committed to maintaining a fair and authentic interview process", "summaryDescription" : "Research Analyst (Non-Data) at DLH. Skills: Public health research, Data analysis, Program management. Ensure capture of program data. 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Austin:1117 Trinity St (320TX-4002)
1117 Trinity St
Austin, 78701-1919

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Internal audits; External audits", "projectManagementSkills" : [ "Strategic planning", "Policy development", "Roadmap planning" ], "domainKnowledge" : "Procurement; Contract management; State data reporting; Federal regulations", "domainList" : [ "procurement", "contract-management", "state-data-reporting", "federal-regulations" ], "domainSpecificKnowledge" : [ "Procurement", "Contract management", "State data reporting", "Federal regulations" ], "toolProficiency" : [ "Dbt Cloud" ], "communicationSkills" : "Executive presentations; Technical documentation; Client meetings", "documentationSkills" : "Technical writing; API documentation; Architecture diagrams", "continuousLearning" : "Training and development opportunities", "innovationCreativity" : "Innovative ideas; Streamline processes", "problemSolvingSkills" : "Problem solver; Root cause analysis; Data-driven decision making", "specialRequirements" : "Texas resident required, Relocate to Texas required", "outcomesObjectives" : "Ensure departmental processes are impartial; Ensure departmental processes are transparent; Ensure departmental processes are professional; Acquisitions of program services for the State", "qualificationsBasic" : "Five years of experience in oversight and direction of an agency or in strategic planning and policy development and implementation, Two years of experience in administrative management or supervisory capacity, Two years of experience in data collection and analysis, One year experience in management and direction of staff relevant to data collection and analysis, Experience with state data reporting and analysis", "qualificationsPreferred" : "PhD preferred, Specific ML framework experience, Cloud platform certs", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Data Analysis and Quality Assurance (DAQA) Director Who We Are: Texas Workforce Commission connects people with careers across the state. We are based in Austin on the east side of the Texas State Capitol, in the Business Operations Division located at 1117 Trinity Street in Austin. We're a Family Friendly Certified Workplace with great work-life balance, competitive salaries, extensive opportunities for training and development, and fantastic benefits. TWC is not considering applications from individuals who require sponsorship for an employment visa, including those with H1B visas or those currently on student or postgraduate visas. You must be a Texas resident to work for the Texas Workforce Commission or willing to relocate to Texas. Who You Are: A self-starting, motivated, collaborative problem solver who understands the value of data analysis in measurement of procurement and contract related activities for the Procurement and Contract Services Department. You should share our department’s mission to provide excellent customer service and ensure that departmental processes are impartial, transparent, and professional. You should be innovative and open to new ideas to streamline existing processes. We strive to ensure that acquisitions of program services are conducted with the best outcome for the State in mind. What you Will Do: The Data Analysis and Quality Assurance (DAQA) Director: -Directs data reporting and analysis activities. -Develops and implements techniques for analyzing and reporting data in meaningful ways and remains compliant with state and federal rules and regulations. -Develops and establishes goals and objectives consistent with the agency policy and procedure. -Provides direction, guidance, and assistance in developing reports and collecting data related to contracts and procurement. -Reviews and approves reports, data collection and analysis, and ensures accuracy and that quality reports are distributed. -Reviews guidelines, procedures, rules, and regulations; and monitors compliance related to contract and procurement databases. -Makes recommendations to improve data collection and analysis. -Plans, develops, and approves schedules, priorities, and standards for achieving goals. -Reviews results of special investigations, internal audits, research studies, forecasts, and modeling exercises to provide direction and guidance. -Performs advanced (senior-level) managerial work providing direction and guidance in strategic operations and planning. Works under minimal supervision, with extensive latitude for the use of initiative and independent judgment. You Will be Trusted To: -Establish goals and objectives. -Respond to audit requests from internal and external entities. -Develop guidelines, procedures, policies, rules, and regulations. -Develop schedules, priorities, and standards for achieving established goals. -Coordinate and evaluate data collection, reporting, and quality. -Develop and evaluate data reports and policies and procedures for producing quality reports and maintaining data integrity. -Plan, assign, and supervise the work of others. -Work under limited supervision, with considerable latitude for the use of initiative and independent judgment. -Performs other duties as assigned. You Qualify With: -Five years of full-time experience in the oversight and direction of an agency program; or in strategic planning and policy development and implementation, two years of which must have been in an administrative management or supervisory capacity. -Relevant academic credits may be applied toward experience qualifications for this position. You Are a Great Fit With: -A minimum of two years’ experience in data collection and analysis. -One year experience in the management and direction of staff relevant to data collection and analysis. -Experience with state data reporting and analysis. You Gain: -A Family Friendly Certified Workplace. -Competitive starting salary: $9,166.67 to $9,583.34/month, depending on experience -Defined Retirement Benefit Plan -Optional 401(k) and 457 accounts -Medical Insurance -Paid time off, including time for vacation, sick and family care leave -Additional benefits for active employees can be found at https://www.ers.texas.gov/Active-Employees/Health-Benefits. VETERANS: Use your military skills to qualify for this position or other jobs! Go to www.texasskillstowork.com to translate your military work experience and training courses into civilian job terms, qualifications, and skill sets. Also, you can compare this position to military occupations (MOS) at the Texas State Auditor's Office by pasting this link into your browser: https://hr.sao.texas.gov/Compensation/MilitaryCrosswalk/MOSC_ProgramManagement.pdf HOW TO APPLY: To be considered, please complete a State of Texas Application for Employment and apply online at www.workintexas.com or on Taleo ( Job Search ). TWC is not considering applications from individuals who require sponsorship for an employment visa, including those with H1B visas or those currently on student or postgraduate visas In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification document form upon hire. A position utilizing this classification will be designated as security sensitive according to the Texas Labor Code, Section 301.042. United States-Texas-Austin", "summaryDescription" : "Data Analysis and Quality Assurance Director at Texas Workforce Commission. Skills: Data analysis, Quality assurance, Data engineering, Machine learning. Direct data reporting and analysis activities. 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Develop training plans", "createdAt" : "2026-06-15T22:17:05.054", "lastUpdated" : "2026-06-16T08:28:10.500", "ingestTimestamp" : "2026-06-15T22:17:05.054", "mongoId" : "6a3058c7f292fd229cf44134", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 42000, "salaryAnnualMax" : 58000, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Track and field", "Youth sports" ], "skillCount" : 2, "jobCategory" : "general", "jobSubcategory" : "general", "seniorityLevel" : "Entry", "dataQualityScore" : 0.44444445, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Education", "llmIndustryConfidence" : 0.85 }, { "id" : "6a2ca07874d8ee00a09a24fe", "title" : "Data Analyst, Product (Banking and Payments)", "company" : "Float", "industry" : "Engineering", "salary" : { "min" : 85000.0, "max" : 115000.0, "currency" : "CAD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Mid-level Data Analyst in Toronto, Canada, adjusted for the FinTech industry." }, "location" : "Toronto, Canada", "locations" : [ "Toronto, Canada" ], "timestamp" : "2026-06-15T09:15:39.904", "fingerprint" : "a1c316db28b7762fa9d4723afbf2a0ddca938382d0dc51344a8e9f8ed3acfe02", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/Float/097f849c-765d-4cac-acf7-898cfa66c20d/application", "externalId" : "097f849c-765d-4cac-acf7-898cfa66c20d", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Toronto", "state" : "Ontario", "country" : "Canada", "continent" : "na", "source" : "llm", "workMode" : "hybrid", "geo" : "43.6534817,-79.3839347" } ], "locationText" : "Toronto, Ontario, Canada", "employmentType" : "FULL_TIME", "technicalSkills" : "SQL, Python, Dbt, Snowflake, AI, LLMs", "professionalSkills" : [ "Product analytics", "Measurement frameworks", "Experiment design", "Data quality audit", "Cohort analysis", "Retention analysis", "Statistical rigor" ], "hardSkillsList" : [ "Statistical analysis", "A/B testing", "Hypothesis testing", "Confidence intervals", "Significance testing" ], "softSkillsList" : [ "Learning velocity" ], "hardSkills" : [ { "name" : "Statistical analysis", "level" : "intermediate" }, { "name" : "A/B testing", "level" : "intermediate" }, { "name" : "Hypothesis testing", "level" : "intermediate" }, { "name" : "Confidence intervals", "level" : "intermediate" }, { "name" : "Significance testing", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Learning velocity" } ], "majorSkills" : "Product analytics, Data quality, Experimentation", "majorSkillsList" : [ "Product analytics", "Data quality", "Experimentation" ], "coreResponsibilities" : "Define measurement needs, Support instrumentation, Translate roadmap decisions, Design measurement frameworks, Align on frameworks, Design experiments, Analyze experiments, Structure A/B tests, Select unit of randomization, Size experiments, Interpret results, Own metrics and dashboards, Keep metrics accurate, Own data quality, Audit dbt models, Write clear briefs, Flag data gaps, Run cohort analysis, Run retention analysis, Diagnose levers, Debug ambiguous numbers, Close the loop, Write expert SQL, Bring statistical rigor, Construct cohorts, Calculate retention, Use LLMs for SQL, Draft frameworks, Structure analysis", "teamCollaboration" : "Product teams; Engineering; Product Marketing; Head of Data", "projectManagementSkills" : [ "Roadmap decisions" ], "domainKnowledge" : "Banking infrastructure; Payments; Fintech; Attach rate; Payment rails; KYC; AP workflows; Pre-authorized payments; Balance/deposit metrics; Churn dynamics", "domainList" : [ "banking-infrastructure", "payments", "fintech", "attach-rate", "payment-rails", "kyc", "ap-workflows", "pre-authorized-payments", "balance-deposit-metrics", "churn-dynamics" ], "domainSpecificKnowledge" : [ "Banking infrastructure", "Payments", "Fintech", "Attach rate", "Payment rails", "KYC", "AP workflows", "Pre-authorized payments", "Balance/deposit metrics", "Churn dynamics" ], "toolProficiency" : [ "Metabase", "Looker", "Tableau", "Sigma" ], "communicationSkills" : "Hold ground respectfully", "problemSolvingSkills" : "Debug ambiguous numbers", "qualificationsBasic" : "2-4+ years product analytics, SQL proficiency, Dbt-comfortable, Snowflake or comparable warehouse", "qualificationsPreferred" : "PhD preferred, Fintech familiarity", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "ABOUT FLOAT Float is on a mission to simplify finance for Canadian businesses, empowering them to eliminate complexity and unlock new opportunities. Through our innovative platform, Float enables businesses to streamline financial operations and optimize cash flow, so they can focus on what matters most: growth. As one of Canada’s fastest growing companies https://www.theglobeandmail.com/business/rob-magazine/top-growing-companies/article-ranking-canadas-top-growing-companies-of-2024/ and top-rated startups in 2025 https://www.linkedin.com/posts/floatfinancial_were-proud-to-share-that-float-has-been-activity-7387093684720300032-2DDz/, 2024 https://www.linkedin.com/pulse/linkedin-top-startups-2024-15-canadian-companies-rise-linkedin-news-llihe/ and 2023 https://lnkd.in/TSU23CA, Float is customer-obsessed, passionate and entrepreneurial, with a team that includes leaders from Uber, Stripe, Shopify, Top Hat, Ada, Doordash, Snowflake, and Wealthsimple. At Float, everyone is an owner, bringing their unique perspective to our team and product. Your voice is important, and we take having a culture based on feedback seriously. We openly share our thoughts and differing opinions so we can continue to improve. We do our best to keep our decision-making decentralized so that all team members feel ownership in our success. OUR PRODUCT Float is Canada's complete business finance platform, combining modern financial services and software to help businesses spend, save, and grow. Trusted by 6000+ Canadian companies, Float provides high-limit corporate cards, automated expense management, next-day bill payments, high-yield accounts and fast, friendly support—all built in Canada, for Canada. Float is backed by world-class venture and fintech investors, including Growth Equity at Goldman Sachs Alternatives and OMERS Ventures, partners behind our $70 million Series B raise https://floatfinancial.com/we-raised-70-million-to-fix-canadas-business-banking-problem/. Our team is a collection of ambitious, collaborative and mission-driven people from all walks of life but with one goal: helping Canadian companies not just survive but thrive. And we’re looking for bold innovators to help shape the future of business finance in Canada. AI USE IN OUR HIRING PROCESS We use technology, including artificial intelligence (AI), to support parts of our hiring process. This may include AI-assisted scheduling and candidate communications, and AI-generated interview notes, guides or summaries to help our team focus on the conversation. All hiring decisions are made by our hiring team. ABOUT THE ROLE Float is building the financial operating system for Canadian businesses — corporate cards, business bank accounts, bill payments, all in one place. Reporting to the Head of Data, this role is embedded inside the product teams behind two of those core pillars: banking infrastructure and payments. Both are high-complexity, high-stakes areas that generate a dense mix of financial, behavioral, and operational data. This role owns that data layer. You're building cohorts before anyone asks, designing measurement frameworks before features go to engineering, and debugging numbers to the source — pipeline issue, definition mismatch, or real product signal. You're also someone who uses AI to move faster without losing rigour. Getting useful outputs from a model means knowing the business and data well enough to give it the right context — that's part of the job too. WHAT YOU'LL BE DOING - Define what needs to be measured before features ship and support the instrumentation to measure it. You translate roadmap decisions into measurement requirements. - Design and get broad alignment on measurement frameworks before features go to engineering — hypothesis, cohorts, success criteria. - Design and analyze experiments - structure A/B tests for product changes. Define the hypothesis, select the right unit of randomization, size the experiment for sufficient power and interpret results with statistical rigour - Own the metrics and dashboards for Banking and Payments. Every number is traceable to a reliable dbt model. You keep them accurate. - Own data quality in your product area — audit dbt models, write clear briefs for analytics engineering, flag gaps before they become problems. - Run cohort and retention analysis natively — activation sequences, behavioral funnels, leading vs. lagging indicators. Diagnose which lever moves the number, not just what happened. - Debug ambiguous numbers to the source — pipeline issue, definition mismatch, or real product signal. You close the loop. - Write expert SQL and bring statistical rigour — cohort construction, retention calculations, confidence intervals, significance testing. You know when you have enough signal to act. - Use AI as a multiplier — accelerate analysis, generate first-pass SQL, and pressure-test hypotheses faster than you could alone. You know how to give a model the business and data context that makes its outputs impactful. - Take your share of ad-hoc requests on rotation — owning your product area gives the broader data team meaningful breathing room. WHAT SUCCESS LOOKS LIKE - Get Embedded: Both team leads treat you as the owner of their data layer. KPI definitions are agreed upon, documented, and tied to reliable dbt models. Gaps are flagged with a fix in motion. - Build the Measurement Layer: Features ship with measurement frameworks designed upfront. Dashboards for the core banking and payments metrics are clean, trusted, and traceable. - Drive Product Evidence: Product decisions are shaped by your analysis before they are made. When a team lead is asked by leadership whether a feature is landing, they already know — because you’ve built the infrastructure that makes the question answerable. WHAT WE'RE LOOKING FOR - Product analytics depth — you've been embedded in a product team, own activation funnels and cohort retention natively, and know how to instrument a feature before it ships. - Experimentation and measurement design — you design A/B tests and quasi-experiments from the ground up: hypothesis, randomization unit, sample size and power calculations, guardrail metrics, and holdout design. You build pre/post and diff-in-diff analyses where randomization isn't feasible, and you know how to communicate the difference in confidence between the two - Data layer ownership — you're the DRI for data quality in your product area: auditing dbt models, writing briefs for analytics engineering, and debugging ambiguous numbers to the source. - Expert-level SQL — you build complex multi-step queries across large behavioral datasets, optimize for performance, and explain the logic to non-technical stakeholders. - Statistical reasoning — you understand distributions, confidence intervals, significance testing, and sample size constraints. You design for confounders, know when you have enough signal, and communicate uncertainty in plain language. - Data modeling literacy — you translate business logic into data requirements, specify the grain a table needs, and have informed opinions on how metrics get structured in dbt. - Comfort with imperfect data — you make a reasoned call, state your confidence level, and give stakeholders something actionable rather than waiting for clean infrastructure. - Stakeholder fluency — you work effectively across Product, Design, Engineering, and Product Marketing, and hold your ground respectfully when data contradicts what the team wants to believe. - AI as an accelerator — you've used LLMs to write SQL, draft frameworks, or structure analysis, and you know where they're reliable and where they need guardrails. - 2–4+ years in product analytics, ideally embedded in a product team at a high-growth fintech or SaaS company. - BI tool experience — Metabase, Looker, Tableau, Sigma, or similar. - dbt-comfortable (reading models, understanding lineage) with Snowflake or a comparable cloud warehouse. - Fintech familiarity — attach rate, payment rails, KYC, AP workflows, pre-authorized payments, balance/deposit metrics, churn dynamics — is a meaningful differentiator. OUR HIRING PHILOSOPHY We hire for character, curiosity, and learning velocity before credentials. Titles matter less than impact, and every hire is expected to raise the bar for Float as a whole. WHY YOU SHOULD JOIN - Work at one of Canada's fastest-growing fintech companies - Make a real impact in a high-autonomy, high-growth role - Collaborate with an ambitious and supportive team - Competitive compensation, equity options, and benefits - Hybrid work model – we are based in Toronto with in-office days for connection and collaboration - Enjoy catered team lunches every Tuesday, Wednesday and Thursday - Bring your pup to our dog-friendly office - Thrive in a high-trust, high-performance culture where your work truly matters IN SHORT At Float, you’ll thrive if you’re bold, curious, and eager to make a real impact. We're building something special—and having a lot of fun along the way. If you’re excited to build, grow, and win together, we’d love to meet you. We’re committed to building a workplace that’s welcoming and accessible for everyone. If you need any accommodations during the hiring process or once you join Float, just let us know! You can reach out to Vic https://www.linkedin.com/in/victoria-boult-b21b2053/ (victoria@floatfinancial.com), and we’ll work with you to make sure you have what you need to succeed.", "summaryDescription" : "Data Analyst, Product (Banking and Payments) at Float. Skills: Product analytics, Data quality, Experimentation. Define measurement needs. Support instrumentation", "createdAt" : "2026-06-14T04:38:39.979", "lastUpdated" : "2026-06-15T09:15:39.904", "ingestTimestamp" : "2026-06-14T04:38:39.979", "mongoId" : "6a2ca07874d8ee00a09a24fe", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "75k-100k", "hasSalary" : false, "allSkills" : [ "Statistical analysis", "A/B testing", "Hypothesis testing", "Confidence intervals", "Significance testing", "Learning velocity", "Product analytics", "Data quality", "Experimentation", "Measurement frameworks", "Experiment design", "Data quality audit", "Cohort analysis", "Retention analysis", "Statistical rigor", "Roadmap decisions", "Banking infrastructure", "Payments", "Fintech", "Attach rate", "Payment rails", "KYC", "AP workflows", "Pre-authorized payments", "Balance/deposit metrics", "Churn dynamics", "Metabase", "Looker", "Tableau", "Sigma" ], "skillCount" : 30, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Mid", "dataQualityScore" : 0.7777778, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.98 }, { "id" : "69fda4e74c40e2acd1b99b8b", "title" : "Data Engineer, AIR DABI (Data Analytics and Business Intelligence)", "company" : "Amazon.com Services LLC", "industry" : "Database Administration, Data Engineering, transportation and logistics", "salary" : { "min" : 101000.0, "max" : 160000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Bellevue, Washington, USA", "locations" : [ "Bellevue, Washington, USA" ], "timestamp" : "2026-06-15T03:34:52.489", "fingerprint" : "f5761f1a8ae6ba0cd457533ce16979448f146e28d2ca815c6657d28a8854a628", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.jobs/jobs/10411675/apply", "externalId" : "93b92467-2d61-4650-83f6-05d9f36c35e2", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Bellevue", "state" : "Washington", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "47.6144219,-122.1923370" } ], "locationText" : "Bellevue, Washington, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala, Python, KornShell, AWS, Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, IAM, Hadoop, Apache Spark, GenAI, LLM", "professionalSkills" : [ "Data modeling", "Database architecture", "Business analysis", "Data transformation", "Data integration", "Data architecture", "Generative AI" ], "hardSkillsList" : [ "ETL processes", "Data integration", "Data pipelines", "Data modeling", "Database management", "Data warehousing", "Data transformation", "Data analysis" ], "hardSkills" : [ { "name" : "ETL processes", "level" : "intermediate" }, { "name" : "Data integration", "level" : "intermediate" }, { "name" : "Data pipelines", "level" : "intermediate" }, { "name" : "Data modeling", "level" : "intermediate" }, { "name" : "Database management", "level" : "intermediate" }, { "name" : "Data warehousing", "level" : "intermediate" }, { "name" : "Data transformation", "level" : "intermediate" }, { "name" : "Data analysis", "level" : "intermediate" } ], "majorSkills" : "Data Engineering, ETL/ELT, AWS, Generative AI", "majorSkillsList" : [ "Data Engineering", "ETL/ELT", "AWS", "Generative AI" ], "coreResponsibilities" : "Design ETL/ELT processes, Implement ETL/ELT processes, Create data integration solutions, Transform business requirements, Develop data pipelines, Maintain data pipelines, Identify data infrastructure challenges, Resolve data infrastructure challenges, Collaborate with cross-functional teams, Drive data-driven decision-making, Contribute to GenAI infrastructure development, Contribute to data foundations development, Design data architectures, Implement data architectures, Support generative AI applications, Support LLM workflows, Leverage GenAI tools, Accelerate development, Accelerate testing", "teamCollaboration" : "Cross-functional teams; Analysts; Business Intelligence Engineers; Data Scientists; SDEs; Business teams", "domainKnowledge" : "Data warehouse environment; Global logistics; Air transportation network; Generative AI applications; LLM workflows", "domainList" : [ "data-warehouse-environment", "global-logistics", "air-transportation-network", "generative-ai-applications", "llm-workflows" ], "domainSpecificKnowledge" : [ "Data warehouse environment", "Global logistics", "Air transportation network", "Generative AI applications", "LLM workflows" ], "toolProficiency" : [ "AWS", "Redshift", "S3", "AWS Glue", "EMR", "Kinesis", "FireHose", "Lambda", "IAM", "Hadoop", "Apache Spark", "Amazon Q" ], "innovationCreativity" : "Technical innovation", "problemSolvingSkills" : "Problem-solving", "qualificationsBasic" : "2+ years data engineering experience, Data modeling experience, Warehousing experience, Building ETL pipelines experience, SQL experience, PL/SQL experience, DDL experience, MDX experience, HiveQL experience, SparkSQL experience, Scala experience, Python experience, KornShell experience, GenAI/LLM tools familiarity", "qualificationsPreferred" : "Data engineer experience, Software engineer experience, Business intelligence engineer experience, Data scientist experience, Manipulating large datasets experience, Processing large datasets experience, Extracting value from large datasets experience, Hadoop experience, Apache Spark experience, Data warehouse technical architecture knowledge, Data warehouse infrastructure components knowledge, ETL knowledge, Reporting tools knowledge, Analytic tools knowledge, Data schema design knowledge, Data schema implementation knowledge, Normalization knowledge, Relational model knowledge, Dimensional model knowledge, Redshift experience, S3 experience, AWS Glue experience, EMR experience, Kinesis experience, FireHose experience, Lambda experience, IAM roles experience, IAM permissions experience, Informatica experience, ODI experience, SSIS experience, BODI experience, Datastage experience", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Do you want to join one of the most exciting teams at the world's most customer-centric company? Then come soar with Amazon Air! AIR's Data, Analytics and Business Intelligence (DABI) team aims to offer the data infrastructure and data applications, processes, and practices that enable the AIR business to leverage its capacity, speed, quality of service, and organic infrastructure to delight Amazon customers worldwide. We are looking for an experienced, innovative Data Engineer to work in a large and complex data warehouse environment. You should be passionate about working with disparate datasets and love bringing data together to answer business questions. You should have deep expertise in creating and managing datasets and a proven ability to translate data into meaningful insights through collaboration with Analysts, Business Intelligence Engineers, Data Scientists, SDEs, and business teams across the Amazon AIR organization. In this role, you will own end-to-end development of data engineering solutions to complex questions and play a critical role in strategic decision-making. The right candidate will possess excellent technical ability in relational database management systems and database architecture, solid business and communication skills, and the ability to work with business owners to develop and define key business questions, collaborate with external data vendors to onboard new datasets, and analyze data effectively. Key job responsibilities - Design and implement robust ETL/ELT processes using AWS big data technologies - Create scalable data integration solutions that transform complex business requirements into actionable insights - Develop and maintain high-performance data pipelines that support critical business intelligence needs - Proactively identify and resolve data infrastructure challenges to enhance system reliability - Collaborate with cross-functional teams to drive data-driven decision-making strategies - Contribute to the development and maintenance of AIR's GenAI infrastructure and data foundations - Design and implement data architectures that support generative AI applications and LLM workflows - Leverage GenAI tools (e.g., Amazon Q, coding assistants) to accelerate development and testing A day in the life Your day will be a dynamic blend of technical innovation and collaborative problem-solving. You'll dive into complex datasets, design elegant data pipelines, and work alongside cross-functional teams to unlock actionable intelligence that shapes the future of global logistics. About the team We are a passionate group of data professionals dedicated to transforming raw information into strategic insights. Our team thrives on collaboration, innovation, and a shared commitment to solving complex challenges that directly impact Amazon's global air transportation network. Basic Qualifications: - 2+ years of data engineering experience - Experience with data modeling, warehousing and building ETL pipelines - Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala) - Experience with one or more scripting language (e.g., Python, KornShell) - Familiarity with leveraging GenAI/LLM tools to improve development productivity Preferred Qualifications: - Experience as a data engineer or related specialty (e.g., software engineer, business intelligence engineer, data scientist) with a track record of manipulating, processing, and extracting value from large datasets - Experience with big data processing technology (e.g., Hadoop or ApacheSpark), data warehouse technical architecture, infrastructure components, ETL, and reporting/analytic tools and environments - Knowledge of basics of designing and implementing a data schema like normalization, relational model vs dimensional model - Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions - Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, WA, Bellevue - 101,300.00 - 160,000.00 USD annually", "summaryDescription" : "Data Engineer, AIR DABI (Data Analytics and Business Intelligence) at Amazon.com Services LLC. Skills: Data Engineering, ETL/ELT, AWS, Generative AI. Design ETL/ELT processes. 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"toolProficiency" : [ "Tableau", "Power BI", "Looker", "Metabase", "Superset", "Qlik", "MicroStrategy" ], "innovationCreativity" : "AI initiatives; AI use", "problemSolvingSkills" : "Root cause analysis; Troubleshooting", "specialRequirements" : "+3 / -7 UTC", "outcomesObjectives" : "Decouple scaling overhead from platform usage growth; Lower cost-to-serve; Equip global teams with data and context; Create measurable business value; Enhance customer-facing product", "qualificationsBasic" : "5+ years of experience, SQL proficiency required", "qualificationsPreferred" : "PhD preferred, GCP Professional Data Engineer certification, AWS Data Analytics certification, Databricks Certified, Dbt Certified", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "✨ ONE PLATFORM, A WHOLE WORLD OF OPPORTUNITY The best jobs are often restricted to a few wealthy cities, but talent exists everywhere. Oyster set out to change this by launching a global employment platform that enables companies to hire, pay, and support talent anywhere. We’re proof that a strong, engaged culture doesn't require an office. Since January 2020, Oyster has: \uD83C\uDF0F Built a distributed team of 400+ across 60+ countries \uD83D\uDC69‍\uD83D\uDCBB Featured in Forbes https://www.forbes.com/sites/laurabegleybloom/2024/01/25/work-from-home-or-anywhere-top-30-companies-for-remote-jobs-in-2024/ as #9 in FlexJobs Top 30 Companies for remote jobs \uD83C\uDF08 Formed a diverse leadership team and a workforce that’s 60% female \uD83C\uDFC6 Earned top employee engagement scores \uD83E\uDD84 Raised $286 million; valued at $1.2 billion \uD83D\uDC9A Achieved B Corp status in 2023 Our momentum shows the power of global employment, and we’re just getting started! If you want to help us drive change and work remotely, we’d love for you to apply! The Role While this position is posted in a specific location, all of Oyster’s positions are fully remote and you can work from home. Forever. To create the best experience for our new hire, this role requires you to be based within +3 / -7 UTC. As the Senior Director, Data Platform and AI, you will own the technical infrastructure and strategic direction that transforms Oyster into an AI-native global platform, decoupling scaling overhead from platform usage growth. Part of our Senior Tech Leadership Team, this highly specialized leadership role unites data platforms, product analytics pipelines, knowledge management, and advanced automation layer frameworks. You will lead the effort to transition AI initiatives from isolated experimentation into centralized systems. This is an organizational transformation role as much as a technical one. You will leverage AI to optimize our internal workflows, modernize our knowledge architecture, and directly enhance our customer-facing product. By building unified data structures and connectivity pipelines, you will directly lower our cost-to-serve and equip our global teams with the clear data and context they need to operate efficiently. Crucially, you will also educate and empower teams across Oyster to scale their own AI use productively. KEY RESPONSIBILITIES - Drive the company-wide AI agenda: scaling local AI initiatives into centralized production systems that create measurable business value. - Own broad, high-impact AI initiatives that have cross functional impact: Moving our AI usage from past narrow or siloed automation examples to execute a company operational transformation. - Partner with Product, Engineering, and operational leaders to embed AI capabilities into our customer-facing platform, internal business workflows, and core processes. - Serve as the ultimate technical authority for our data and AI infrastructure, making critical architectural decisions across MLOps pipelines, LLM orchestration frameworks, and distributed data systems. - Oversee the development of a scalable corporate data platform that serves as the foundational bedrock for all AI and machine learning capabilities. - Transform our internal knowledge base by building the systemic data architecture needed to turn unstructured information into intelligent, easily searchable, and actionable assets. - Re-build and evolve our company-wide data structures and connectivity pipelines to be optimized to deploy, run, and maintain AI models efficiently while lowering cost-to-serve. - Set the company wide tooling standards, maintain technical quality guardrails, and establish engineering best practices for embedded AI specialists working within distinct business units. - Actively support the implementation of key local solutions built by decentralized specialists, ensuring they have the tools and centralized platform support required to succeed. - Maintain high levels of ethical compliance by ensuring all global AI initiatives strictly adhere to data privacy, platform security, and ethical compliance standards. - Educate and empower teams across the organization to scale their own AI use productively, providing them with the structural frameworks needed to safely build and innovate within their functions. - Partner deeply with the People and Operations functions to champion organizational AI capability, replacing operational uncertainty with structured technical training loops that convert manual specialists into power-users of automated solutions. - Drive the organizational change management and literacy efforts required to reshape daily workflows, shifting company culture and habits from traditional manual processes to AI-assisted operations. CORE REQUIREMENTS - A genuine passion for artificial intelligence that goes far beyond product feature delivery. You possess a demonstrated interest in, and concrete evidence of driving, internal organizational change, specifically regarding how AI reshapes day-to-day employee workflows and habits. - Proven experience operating within a service-delivery model or a highly complex operational business, where data strategy directly impacts intricate, real-world workflows and diverse stakeholder ecosystems. - A history weighted heavily toward data engineering, distributed systems development, platform services infrastructure, or system architecture over front-end application product design. - A proven deep technical track record in distributed data systems, MLOps pipelines, and LLM orchestration. You can easily evaluate complex models and emerging technologies, serving as the ultimate technical authority for our infrastructure. - Documented success building, testing, and scaling complex asynchronous data structures, machine learning routing layers, or high-volume API integrations within modern software platforms. - The ability to view the organization holistically. You use your understanding of how interconnected technical platforms, business processes, and human teams interact, designing data and AI solutions that optimize entire workstreams rather than individual silos. - A proven track record of driving internal adoption for major technology or workflow shifts. You can break down complex AI frameworks for non-technical teams, guide employees through operational transitions, and successfully shift daily habits from manual work to AI-assisted processes. - Comprehensive familiarity with model validation systems, technical anomaly logging, data pipeline health metrics, and automated governance frameworks (e.g., custom logging models or open-source pipeline validation stacks). - BONUS : Background architecting semantic search solutions, internal retrieval-augmented generation engine layers, or multi-tenant customer data structures from zero-to-one phases. You'll also need - A reliable home internet connection and fluency in both written and spoken English HOW WE WORK TOGETHER AT OYSTER Our values guide the work we do, the decisions we make, and the culture that makes us special. We make it happen. We drive change. We build and give trust, and we are a united team. Our mission is to create a more equal world, one global hire at a time. Everything we do ladders up to our mission, and that doesn’t just mean building software. We develop programs, participate in workshops, and create dedicated teams to ensure we successfully support companies and knowledge workers in this new world of work. We embrace asynchronous communication and collaborative work and share our practices in the Oyster Public HQ https://oysterhr.notion.site/Welcome-to-The-Reef-Oyster-s-Open-Source-Employee-Guide-fc482e3f107c4afd8c85ed217f1d0c1d to help other global teams learn from our experiences. HOW YOU WORK With diverse locations, cultures, and needs, we created How YOU Work; https://oysterhr.notion.site/How-YOU-work-ac16c1932e314ffd8cb693e332458395 a program supporting your whole human experience at Oyster: - Work from anywhere: Oyster has no borders or HQ. As long as work is timely, your team is supported, and you're authorized to work where you live, you can work from anywhere. - Paid time off: Enjoy 40 days off per year (including holidays and vacation), or more if required by your country. - Mental health support: Access Plumm https://oysterhr.notion.site/Plumm-3b5e7e70dec6428e975f68f25972cfb7, our mental well-being service. - Wellbeing allowance: Each month, receive a wellbeing allowance in your ThanksBen wallet. Spend it on a wide range of options; see the benefits catalogue https://www.thanksben.com/employee-benefits-catalogue for ideas. - Flexible parental leave: All new parents are eligible for at least three months’ paid leave, with job protection for up to 12 months or as required locally. - WFH stipend: Receive a stipend for your laptop and home office equipment to get you set up quickly. ✨ THE BEST JOBS SHOULD BE AVAILABLE TO EVERYONE We embrace diverse perspectives and intentionally build our product and company with an inclusive, global mindset. We encourage you to apply, even if you don’t meet every criterion, and are committed to a trust-based, thriving environment. Oyster is committed to ensuring equal opportunity of employment for qualified persons with disabilities and actively fosters an inclusive work environment. If you require reasonable accommodations throughout the recruiting process, please email jobs@oysterhr.com with the subject line: Interview Accommodations. 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[Mountain View, CA, USA, [Mountain View, CA, USA], Mountain View, null, CA, US]", "technicalSkills" : "SQL, Python, R, Spark, AWS, GCP, Azure, SageMaker, Vertex AI, ML Studio, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow, Tableau, Power BI, Looker", "professionalSkills" : [ "Data modeling", "Statistical analysis", "Machine learning", "Business intelligence", "Analytics engineering", "Quantitative analysis" ], "hardSkillsList" : [ "Regression", "Classification", "Clustering", "Time-series analysis", "A/B testing", "Causal inference" ], "hardSkills" : [ { "name" : "Regression", "level" : "intermediate" }, { "name" : "Classification", "level" : "intermediate" }, { "name" : "Clustering", "level" : "intermediate" }, { "name" : "Time-series analysis", "level" : "intermediate" }, { "name" : "A/B testing", "level" : "intermediate" }, { "name" : "Causal inference", "level" : "intermediate" } ], "majorSkills" : "Applied Machine Learning, Data Science, Business Intelligence, Marketing Analytics", "majorSkillsList" : [ "Applied Machine Learning", "Data Science", "Business Intelligence", "Marketing Analytics" ], "coreResponsibilities" : "Develop and deploy machine learning models, Analyze marketing campaign performance, Build and maintain data pipelines, Create dashboards and reports, Collaborate with marketing and product teams, Communicate findings to stakeholders", "teamCollaboration" : "Marketing teams; Product teams; Cross-functional teams", "domainKnowledge" : "Marketing analytics; Customer segmentation; Campaign optimization; Marketing attribution", "domainList" : [ "marketing-analytics", "customer-segmentation", "campaign-optimization", "marketing-attribution" ], "domainSpecificKnowledge" : [ "Marketing analytics", "Customer segmentation", "Campaign optimization", "Marketing attribution" ], "toolProficiency" : [ "Dbt", "Fivetran", "Airflow", "Dbt Cloud", "Delta Lake" ], "communicationSkills" : "Present findings; Communicate insights", "documentationSkills" : "Document models; Document pipelines", "problemSolvingSkills" : "Analytical thinking; Problem-solving", "qualificationsBasic" : "5+ years of experience in data science, Proficiency in SQL, Proficiency in Python or R", "qualificationsPreferred" : "PhD in a quantitative field, Experience with cloud platforms (AWS, GCP, Azure), Experience with ML frameworks (scikit-learn, TensorFlow, PyTorch), Experience with BI tools (Tableau, Power BI, Looker)", "summaryDescription" : "Business and Marketing Data Scientist, Applied Machine Learning. Skills: Applied Machine Learning, Data Science, Business Intelligence, Marketing Analytics. Develop and deploy machine learning models. Analyze marketing campaign performance", "postedDate" : "2026-06-16T01:48:48.533", "createdAt" : "2026-06-16T01:48:48.533", "lastUpdated" : "2026-06-16T11:24:18.072", "ingestTimestamp" : "2026-06-16T01:48:48.533", "mongoId" : "6a307f05f292fd229c0547e3", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "hasSalary" : false, "allSkills" : [ "Regression", "Classification", "Clustering", "Time-series analysis", "A/B testing", "Causal inference", "Applied Machine Learning", "Data Science", "Business Intelligence", "Marketing Analytics", "Data modeling", "Statistical analysis", "Machine learning", "Business intelligence", "Analytics engineering", "Quantitative analysis", "Marketing analytics", "Customer segmentation", "Campaign optimization", "Marketing attribution", "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified", "Dbt", "Fivetran", "Airflow", "Dbt Cloud", "Delta Lake" ], "skillCount" : 29, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Mid", "dataQualityScore" : 0.44444445, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustryConfidence" : 0.0 }, { "id" : "6a308587f292fd229c079aa0", "title" : "Field Service and Technical Advising Specialist", "company" : "Wabtec", "industry" : "Railroad Manufacture", "salary" : { "min" : 1.5E7, "max" : 2.5E7, "currency" : "GNF", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Field Service and Technical Advising Specialist in Conakry, Guinea, adjusted for the manufacturing industry and company size." }, "location" : "Conakry, GN", "locations" : [ "Conakry", "GN" ], "timestamp" : "2026-06-16T11:26:45.768", "fingerprint" : "168d428a3708dfdebc25b8e7c0a6a1ab5ac401dc0639f0baffc2a58110cfad03", "source" : "smartrecruiters", "language" : "en", "applyUrl" : "https://jobs.smartrecruiters.com/Wabtec/3743990013615566-field-service-and-technical-advising-specialist", "externalId" : "3743990013615566", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Conakry", "country" : "Guinea", "continent" : "af", "source" : "llm", "workMode" : "onsite", "geo" : "9.5170602,-13.6998434" } ], "locationText" : "Conakry, Guinea", "employmentType" : "FULL_TIME", "experienceLevel" : "not-applicable", "technicalSkills" : "Mechanical design, Electrical design, Control systems, Product development, CAD software, Simulation tools", "professionalSkills" : [ "Problem-solving", "Analytical skills", "Technical communication" ], "hardSkillsList" : [ "Mechanical engineering", "Electrical engineering", "Control theory", "Product lifecycle management" ], "hardSkills" : [ { "name" : "Mechanical engineering", "level" : "intermediate" }, { "name" : "Electrical engineering", "level" : "intermediate" }, { "name" : "Control theory", "level" : "intermediate" }, { "name" : "Product lifecycle management", "level" : "intermediate" } ], "majorSkills" : "Mechanical design, Electrical design, Control systems", "majorSkillsList" : [ "Mechanical design", "Electrical design", "Control systems" ], "coreResponsibilities" : "Design mechanical components, Design electrical systems, Develop control strategies, Oversee product development lifecycle, Collaborate with cross-functional teams, Conduct design reviews, Perform system testing, Troubleshoot technical issues", "teamCollaboration" : "Cross-functional teams; Engineering teams; Manufacturing teams; Sales teams", "projectManagementSkills" : [ "Project management", "Product development planning" ], "domainKnowledge" : "Industrial automation; Robotics; Mechatronics", "domainList" : [ "industrial-automation", "robotics", "mechatronics" ], "domainSpecificKnowledge" : [ "Industrial automation", "Robotics", "Mechatronics" ], "toolProficiency" : [ "CAD software", "Simulation tools", "Project management software" ], "communicationSkills" : "Technical documentation; Design reviews; Project updates", "documentationSkills" : "Technical documentation; Design specifications; Test reports", "problemSolvingSkills" : "Root cause analysis; Troubleshooting; Design optimization", "outcomesObjectives" : "Deliver high-quality designs; Ensure product functionality; Meet project deadlines; Reduce product development costs", "qualificationsBasic" : "Bachelor's degree in Engineering, 5+ years of experience, Experience with mechanical design, Experience with electrical design, Experience with control systems, Experience with product development", "qualificationsPreferred" : "Master's degree preferred, Experience with CAD software, Experience with simulation tools, Experience with project management software", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Technical Advisor - FIFO Job Summary: The Technical Advisor will provide Wabtec Locomotive technical advice to Wabtec subcontracted maintenance staff for all covered locomotives on the customer rail network. Successful candidate will, amongst others: Ensure that locomotive servicing are completed in a timely manner, safely and to the agreed Maintenance Instructions (MI’s); Provide trouble shooting advice to maintenance technical personnel; Work closely with Reliability Engineers to improve key locomotive performance KPI’s; Ensures material is provided by the Wabtec material management team ‘Just in Time’ (JIT) for all maintenance opportunities; Works closely with the other relevant stakeholders to ensure all locomotives that depart customer maintenance shops are best prepared to complete 100% successful journeys; Engage and discuss Wabtec technical products with customer and subcontracting team to improve reliability / productivity and other KPIs. This role will be based in Guinea near the port of Morebaya on a rotational basis(FIFO) of 60 days on and 15 days off. The operation is 24/7 running two 12 hour shifts. Accommodation will be provided at the facility. Mobilization and demobilization, air and land transportation will be provided. This role will be eligible for an assignment allowance and overtime. Main Duties: Reporting directly to the Lead Technical Advisor this role will; * Respond and execute on requests for planned and unplanned maintenance, troubleshooting, failure analysis, field modification oversight, issue feedback and engineering support; * Providing training and assistance to customers and subcontractor on product maintenance, troubleshooting and repair to ensure maintenance best practice compliance and according to Wabtec MIs. * Ensure that Maintenance management system is accurately updated during assigned shift. * Track and forecast material and consumables usage * Track product performance metrics and issue recommendations for continuous improvement. * Coordinating implementation of field modifications and monitor effectiveness. * Performing joint investigation of failed components. * Interaction with Wabtec teams worldwide on technical issues, product development and training. * Participate during Wabtec Internal and external reporting * Ensure timely resolution of customer issues and customer satisfaction * Develop a deep understanding of the customer’s business to identify opportunities for account growth and improvements * Participate and contribute during EHS initiatives to ensure work is conducted in a safely manner. Desired Characteristics * Proven analytical and organizational ability. * Ability to lead initiatives of moderate scope and impact. * Effective problem identification and solution skills * Lean/Six Sigma certification * High level of dependability, a great attitude, and an ability to work well with a team towards achieving common goal. * Proven ability to work well withing a diverse team. ## Qualifications Minimum Requirements * Bachelors’ Degree in a Technical discipline from an accredited College or University. * Minimum of 5 years in customer facing locomotive services role- Wabtec locomotives * L1 Locomotive Technical Training certification * Experience, willingness, and ability to work in shop environment and to work various shifts on various days as required. * Understanding of Wabtec Maintenance and Material management processes and systems. * Strong leadership and Interpersonal skills * Ability to interface with different levels of internal and external stakeholders. * Fluent in English, French or Mandarin ## Additional Information What could you accomplish in a place that puts People First? At Wabtec, it’s not just about a job - it’s about the impact you make. When our people come together, we’re Expanding the Possible by continuously improving what we do and how we do it - for our clients and each other. If you’re ready to revolutionize how the world moves for future generations, Wabtec is the place for you. Who are we? Wabtec is a leading global provider of equipment, systems, digital solutions, and value-added services for the freight and transit rail sectors. Drawing on more than 150 years of experience, we are leading the way in safety, efficiency, reliability, innovation, and productivity. Whether it’s freight, transit, ports, logistics, mining, industrial, or marine, our expertise, technologies, and people together – are accelerating the future of transportation. With roots that date back to George Westinghouse, Thomas Edison, and Louis Faiveley, Wabtec has always built technologies and implemented solutions for a variety of sectors that are critical to meeting the needs of customers and governments alike. Our global team of about 30,000 employees worldwide delivers performance that moves the world forward. We’re lifelong learners, obsessed with better. Learn more at www.WabtecCorp.com. Culture powers us and the possibilities. We believe the best ideas come from a mix of experiences and backgrounds. At Wabtec, we strive every day to create a place where everyone belongs. We’re building a culture where leadership, inclusion and your unique perspective fuel progress. We’re proud to be an Equal Opportunity Employer. We welcome talent of all backgrounds, experiences, and identities, including race, gender, age, disability, veteran status and more. Need accommodation? Just let us know - we’ve got you.", "summaryDescription" : "Field Service and Technical Advising Specialist at Wabtec. Skills: Mechanical design, Electrical design, Control systems. Design mechanical components. Design electrical systems", "postedDate" : "2026-06-15T09:46:03.000", "createdAt" : "2026-06-16T01:36:49.514", "lastUpdated" : "2026-06-16T11:26:45.768", "ingestTimestamp" : "2026-06-16T01:36:49.514", "mongoId" : "6a308587f292fd229c079aa0", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Mechanical engineering", "Electrical engineering", "Control theory", "Product lifecycle management", "Mechanical design", "Electrical design", "Control systems", "Problem-solving", "Analytical skills", "Technical communication", "Project management", "Product development planning", "Industrial automation", "Robotics", "Mechatronics", "CAD software", "Simulation tools", "Project management software" ], "skillCount" : 18, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Senior", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Manufacturing", "llmIndustryConfidence" : 0.95 } ], "status" : 200, "message" : "correlate and interpret data obtained from field data and research jobs", "metadata" : { "title" : "correlate and interpret data obtained from field data and research" }, "pagination" : { "page" : 0, "limit" : 50, "totalCount" : 51054, "totalPages" : 1022, "hasNext" : true, "hasPrevious" : false } }

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