Senior Data Scientist, AI Enablement

About Oscar

Oscar is the first health insurance company built around a full stack technology platform and a relentless focus on serving our members. We started Oscar in 2012 to create the kind of health insurance company we would want for ourselves—one that behaves like a doctor in the family.

About the Role

As a Senior Data Scientist for AI Enablement, you will sit at the intersection of data science, data engineering, and artificial intelligence. You will design, build, and maintain AI-powered analytical systems and pipelines that empower internal stakeholders to self-serve their data needs. This builder-focused role requires turning ambiguous workflows into well-engineered, LLM-augmented data tools and automated insights.

You will act as a foundational driver for AI Enablement for Data, operating with a high degree of independence to take projects from conception to launch. You will partner closely with AI engineers, software engineers, data scientists, and business stakeholders.

You will report to the Director, Data Science.

Work Location

This position is based in our New York City office, requiring a hybrid work schedule with 3 days of in-office work per week (Thursdays are required; the other two days are flexible).

Responsibilities

• Lead the design, development, and deployment of AI-driven self-serve analytics products, from zero-to-one prototypes to robust production systems.
• 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 ambiguous questions and unsupported conclusions.
• Collaborate cross-functionally with AI engineers, software engineers, and business leaders to integrate data workflows into broader software applications.
• Help shape Oscar’s technical direction and roadmap for AI-enabled analytics.
• Ensure compliance with all applicable laws and regulations.

Requirements

• 4+ years of experience in industry or other quantitative technical fields (which may include academia).
• 3+ years of experience working with SQL and Python to query, manipulate, and analyze 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 such as version control, code review, and testing.
• Experience acting as a primary driver of technical projects, operating independently to scope and deliver solutions end-to-end.

Bonus Points

• Experience integrating advanced agentic workflows into analytical tools and automated pipelines.
• Experience with the healthcare industry and familiarity with claims or clinical data.
• Experience with headless semantic layers, such as Cube or MetricFlow.
• Profile as a data scientist with an AI engineering background or an AI engineer with a data science background.