Oscilar
Finance
AnalyticsEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Analytics Engineer at Oscilar. Skills: Analytics Engineering, Data Pipelines, AI Fluency, SQL. Understand stakeholder data needs. Translate needs into technical requirements”
What You'll Achieve.
Build the data foundation for scalable analytics; Ensure access to accurate, trusted data; Ensure timely and accurate data delivery; Enable self-serve analytics across the company; Making the internet safer
Industry & Context.
Solving complex problems; Full-stack mindset
What They're Looking For.
Must Have
5+ years of experience as an Analytics Engineer, Data Engineer, or in a similar Data Science & Analytics role, Experience partnering with GTM, Finance, and cross-functional leaders to build and report on company-wide metrics, SQL and Python skills, Experience building multi-step ETL workflows and robust data models using tools like dbt, AI fluency, with hands-on experience using tools like Claude, LLMs, and/or AI agents to accelerate technical analytics, data engineering, automation, or reporting workflows, Ability to use AI-generated code and analysis effectively while independently reviewing, debugging, and validating the underlying logic, Familiarity with workflow orchestration tools like Airflow, Familiarity with version control tools like GitHub, Experience building reporting and dashboards in visualization tools like Hex, Claude-powered workflows, or similar platforms, data integrity mindset, with experience building reliable data pipelines, metric definitions, QA processes, and reporting standards, judgment on build vs. buy decisions, with the technical ability and willingness to build lightweight tools, workflows, and automations yourself when needed, Experience in a scaled, high-performing analytics or data environment, with a clear understanding of what best-in-class looks like, Full-stack mindset, with a willingness to solve problems end-to-end even when they fall outside a narrow job description
Nice to Have
AI Risk Decisioning™ Platform experience, Experience in a scaled, high-performing company, Experience building in a fast-moving startup environment, Deep AI fluency
What You'll Do.
Understand stakeholder data needs
Translate needs into technical requirements
manage data pipelines
Use AI tools to accelerate workflows
Establish data integrity standards
Develop reliable dashboards
Build foundational data products
Bring point of view on build vs. buy
Partner with leaders to influence roadmap
Become expert in Oscilar's data
Help shape analytics function
How You'll Work.
Team & Collaboration
Partner closely with stakeholders across Ops, Finance, and the GTM org; Partner with GTM and Finance leaders
Full Job Description
At Oscilar, we're building the most advanced AI Risk Decisioning™ Platform. Banks, fintechs, and digitally native organizations rely on us to manage their fraud, credit, and compliance risk with the power of AI. If you're passionate about solving complex problems and making the internet safer for everyone, this is your place https://oscilar.com/careers. ROLE OVERVIEW As an Analytics Engineer, you will be a foundational member of Oscilar’s GTM Ops & Strategy team, helping build the data foundation for scalable analytics across the organization. You will partner closely with stakeholders across Ops, Finance, and the GTM org, including Sales, Marketing, BDR, and Customer Success, to transform raw data into reliable metrics, reporting, and insights. You will be responsible for ensuring teams have access to accurate, trusted data that scales with the company’s growth. This role is ideal for someone who combines strong technical analytics fundamentals with deep AI fluency. You should be comfortable using Claude, LLMs, and AI agents to accelerate end-to-end analytics workflows, from requirements gathering and data modeling to analysis, dashboarding, documentation, QA, and automation. At the same time, you should have the technical judgment to read, write, debug, and validate code yourself, knowing where AI can move faster and where human review is essential. We are looking for someone who knows what best-in-class data and analytics infrastructure looks like, ideally from experience in a scaled, high-performing company, but who is also excited to build in a fast-moving startup environment. You should be nimble, hands-on, and opinionated about when to build versus buy, with the ability to build lightweight internal tools, workflows, and analytics products yourself when that is the fastest or highest-leverage path. KEY RESPONSIBILITIES - Understand stakeholder data needs across Ops, Finance, and the GTM org, including Sales, Marketing, BDR, and Customer Success, and translate
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