Senior Data Scientist - Risk Adjustment

Hi, we're Oscar. We're hiring a Senior Data Scientist 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. The Risk Adjustment Data Science team turns that data into the models, pipelines, and systems that quantify Oscar's clinical risk and power our risk adjustment submissions—work that directly impacts Oscar's financial performance and strategic decision-making.

As a Senior Data Scientist on this team, you will design, build, and maintain systems that automate manual business processes across the risk adjustment space. Our Actuarial team will be your core stakeholders, and you will also partner with our internal Risk Adjustment team and other business functions. You will work closely with these stakeholders to understand their processes, then bring those workflows into our data science infrastructure—re-engineering them to be more robust, accurate, and feature-rich. This is a builder-focused role: the ideal candidate is energized by taking an ambiguous, manual process and turning it into well-engineered, validated, and maintainable production systems.

You will own projects end-to-end—scoping problems with stakeholders, designing the technical approach, implementing pipelines and models, validating outputs against existing processes, and iterating after launch. Beyond individual projects, you will help shape the technical direction of the team's risk adjustment models and infrastructure, and provide informal mentorship to junior data scientists.

You will report to the Senior Manager, Data Science on the Risk Adjustment team.

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:

• Designs, builds, and maintains production data pipelines, and analytical systems supporting Oscar's clinical risk adjustment quantification and submissions processes
• Partners closely with business stakeholders including the Actuarial and Risk Adjustment teams—to translate manual processes into automated, validated, and feature-rich systems
• Owns projects end-to-end, including problem definition, technical design, implementation, validation against existing processes, and post-launch iteration
• Interacts and collaborates closely with data and business counterparts across functional areas
• Works with team and manager to impact longer term strategies and roadmap
• Provides informal mentorship to junior data scientists
• 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 work experience working with SQL and Python to query, manipulate, and analyze data
• 3+ years 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

Bonus points:

• Advanced degree in a quantitative or technical field
• Experience in the healthcare, finance and/or insurance industries
• Experience with risk adjustment, actuarial processes, or health insurance financial modeling
• Experience converting manual or spreadsheet-based analytical processes into automated production systems
• Experience with modern data and orchestration tooling (e.g., BigQuery, dbt, Dataflow) and cloud platforms