OneMagnify
DataScientist
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Data Scientist at OneMagnify. Skills: Data science, Predictive modeling, Data integration, Analytics. Design analytical models. Deploy analytical models”
What You'll Achieve.
Drive measurable outcomes; Build analytics capabilities at scale; Reproduce, maintain, and extend code
Industry & Context.
Root-cause analysis; Data-quality issues
What They're Looking For.
Must Have
BAS in Computer Science, Statistics, Mathematics, MIS, Marketing Research, or related quantitative field, 2–5+ years of hands-on analytics, Advanced SQL, Databricks experience, Tableau and/or Power BI proficiency, Git/GitLab experience, Excel and PowerPoint skills, Ability to present analyses to management, Collaborate with business and technical stakeholders, Experience diagnosing and resolving data-quality issues, Understanding of data governance, privacy, and compliance standards
Nice to Have
SAS or R proficiency, Automotive or VIN data familiarity, AI-enabled analytics workflows exposure, Experience in integrated marketing, consulting, or digital services
What You'll Do.
Design analytical models
Deploy analytical models
Monitor analytical models
Conduct causal analyses
Develop optimization solutions
Ensure model reproducibility
Integrate data from multiple sources
Develop data-quality reporting
Conduct root-cause analysis on data anomalies
Validate database changes
Process large-scale data
Execute machine learning workflows
Partner with business teams
Partner with engineering teams
Define business rules
Turn requirements into technical specifications
Ensure alignment between client requests and built solutions
Synthesize analytical findings
Present analytical findings
Build metrics reports
Prepare visualizations
Use Git for version control
Collaborate on code development
Implement MLOps practices
Manage end-to-end model lifecycle
Adhere to data governance standards
Adhere to data privacy standards
Adhere to compliance standards
How You'll Work.
Team & Collaboration
Cross-functional teams; Engineering teams; Strategy teams; Delivery teams; Internal stakeholders; External stakeholders; Business stakeholders; Technical stakeholders
Communication Scope
Present findings; Handle inquiries; Build reports; Prepare visualizations
Full Job Description
# Data Scientist ## Role Summary OneMagnify's Data Scientists sit at the intersection of client strategy and technical delivery, turning complex business questions into models, analyses, and insights that clients actually use to make decisions. You'll work alongside Data Engineering, AI, and cross-functional teams to design and deploy solutions that span the full analytics lifecycle, from data integration and quality to predictive modeling and advanced analytics. This role is a fit for someone who wants to do serious technical work and see it matter in the real world. ## The Impact You'll Have The clients you'll support are making high-stakes decisions about customers, markets, and products. Your models, including forecasting demand, segmenting audiences, and optimizing spend, become the analytical backbone of how they operate. When your work is right, it drives measurable outcomes. When it's wrong, someone notices. That accountability is part of what makes this role interesting. You'll also contribute to building the analytics capabilities OneMagnify delivers at scale. That means writing code and documentation that others can reproduce, maintain, and extend. Shipping a model is the beginning, not the end. Cross-functional collaboration with engineering, strategy, and delivery teams is part of the daily rhythm, and your ability to translate between technical and business contexts will be used constantly. The work spans industries and problem types (automotive, retail, financial services, and more) so you'll develop breadth alongside depth. You'll rarely work on the same type of problem twice in a row. ## What You'll Do **Build and validate analytical models** * Design, deploy, and monitor models including forecasting, classification, regression, and segmentation * Conduct A/B testing and causal analyses with rigorous experimental design and clear documentation * Develop optimization solutions (linear, mixed-integer, multi-objective) and ensure reproducibility across
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