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Salary: USD 163,944 - 215,176.5 / annual
Oscar Health is seeking a Senior Data Scientist for AI Enablement to join its Data Team in New York. This is a builder-focused role at the intersection of data science, data engineering, and artificial intelligence.
You will design, build, and maintain AI-powered analytical systems and pipelines that enable internal stakeholders to self-serve their data needs. Oscar's data team works with a rich trove of healthcare and insurance data spanning financial claims, clinical medical records, and member product interaction data. Your mission is to turn ambiguous workflows into well-engineered, LLM-augmented data tools and automated insights.
Key responsibilities include:
- Lead the design, development, and deployment of AI-driven self-serve analytics products from prototype to production.
- Rapidly experiment with new models, techniques, and tools, selecting approaches based on measured quality, reliability, performance, and cost.
- Establish evaluations and monitoring for analytical accuracy, generated queries, and AI-generated insights, including handling of ambiguous questions and unsupported conclusions.
- Collaborate cross-functionally with AI engineers, software engineers, and business leaders to understand user needs and integrate data workflows into broader software applications.
- Help shape Oscar's technical direction and roadmap for AI-enabled analytics.
- Operate with high independence, taking projects from conception to launch while partnering closely with cross-functional teams.
You will report to the Director, Data Science. The role requires 3 days per week in the New York City office (hybrid), with Thursdays as a mandatory in-office day for team meetings.
Requirements:
- 4+ years of experience in industry or other quantitative technical fields (including academia).
- 3+ years of experience with SQL and Python for querying, manipulating, and analyzing data.
- 2+ years of experience with LLMs, prompt engineering, and GenAI concepts, with a track record of applying them to practical use cases.
- Experience building data models using advanced analytics methods, statistical modeling, and/or data processing.
- Experience designing, building, and maintaining production data pipelines or systems, applying software engineering best practices (version control, code review, testing).
- Experience acting as a primary driver of technical projects, operating independently to scope and deliver end-to-end solutions.
Bonus qualifications:
- Experience integrating advanced agentic workflows into analytical tools and automated pipelines.
- Healthcare industry experience; familiarity with claims or clinical data.
- Experience with headless semantic layers (Cube, MetricFlow).
- Background as a data scientist with AI engineering skills or vice versa.
