Senior Data Scientist, Advanced Risk Modeling

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:

The Senior Data Scientist, Advanced Risk Modeling, is a senior individual contributor role focused on utilizing advanced machine learning (ML) and artificial intelligence (AI) methodologies on modern ML platforms. This role will build and deploy sophisticated models to help solve complex business problems specifically within Oscar's risk adjustment domain.

You will report into the Director of Data

Work Location: This position is based in our Tempe 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: $158,400- $207,900 per year. You are also eligible for employee benefits, participation in Oscar's unlimited vacation program, company equity grants, and annual performance bonuses.

Responsibilities:

• Conduct in-depth data analysis and advanced feature engineering using large, complex healthcare datasets to create robust predictors.
• Design, develop, and validate advanced ML/AI models (e.g., regression/classification, deep learning, NLP, gradient boosting, LLM experimentations) to solve complex clinical and business problems within the risk adjustment domain.
• Leverage modern ML Ops platforms (e.g., Vertex AI) and data science best practices to efficiently train, test, deploy, and maintain production-level models.
• Build and maintain the supporting data systems, analytics, and monitoring infrastructure required for complex, production-level AI/ML systems.
• Research, develop, and evaluate new AI applications using cutting-edge techniques, including LLM models and agentic frameworks, to solve critical business challenges in risk adjustment.
• Work closely with business stakeholders, engineering teams, and product managers to gain a deep understanding of business operations and technical systems.
• Build strong partnerships to foster close, effective integrations between data science, engineering, product, and business units.
• Partner with leaders to identify high-impact opportunities, translate complex business challenges into data science solutions, and ensure successful model implementation within business workflows.

Requirements:

• 4+ years of industry or other quantitative technical fields (which may include academia).
• 3+ years of work experience working with SQL, R, and/or Python to query, manipulate and analyze data
• 3+ years experience building data models, using more advanced analytics methods, statistical modeling, and/or data processing

Bonus points:

• Advanced degree in a quantitative or technical field
• Experience in the healthcare, finance and/or insurance industries