Senior Data Scientist - AI Enablement

Hi, we're Oscar. We're hiring a Senior Data Scientist, AI Enablement to join our Data Team.

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:

Oscar's data team is focused on pushing our understanding of the complex landscape of the healthcare and insurance business. Insurance companies sit on a trove of data that is both broad and deep—spanning financial claims, clinical medical records, and rich product interaction data from our members. 

As a Senior Data Scientist for AI Enablement, you will sit at the intersection of data science, data engineering, and artificial intelligence. You will be responsible for designing, building, and maintaining AI-powered analytical systems and pipelines that empower our internal stakeholders to self-serve their data needs. This is a builder-focused role: the ideal candidate is a data scientist with a strong engineering background (or vice versa) who is energized by 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. You will be expected to operate with a high degree of independence, taking projects from initial conception to launch. While you will own these workflows end-to-end, you won’t be building in a silo. This is a highly cross-functional position where you will partner closely with a talented group of AI engineers, software engineers, data scientists, and business stakeholders to bring scalable, production-ready solutions to life.

You will report into 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 a required in-office day for team meetings and events, while your other two office days are flexible to suit your schedule. #LI-Hybrid

Pay Transparency: The base pay for this role is: $163,944 - $215,176.50 per year. You are also eligible for employee benefits, participation in Oscar's unlimited vacation program, company equity grants, and annual performance bonuses.

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 how systems handle ambiguous questions and unsupported conclusions.
• Collaborate cross-functionally with AI engineers, software engineers, and business leaders to deeply understand user needs and seamlessly integrate your data workflows into broader software applications.
• Help shape Oscar’s technical direction and roadmap for AI-enabled analytics.
• Compliance with all applicable laws and regulations.
• Other duties as assigned.

Requirements:

• 4+ years of 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 more 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 from end-to-end.

Bonus points:

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