Senior Data Scientist, Advanced Risk Modeling

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Data ScienceData ScientistDataData & AI

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Quick Summary

Key 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.,

Requirements Summary

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,

Technical Tools

Data ScienceData ScientistDataData & AI

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

~1 min read

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

Responsibilities

~1 min read

→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

~1 min read

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

Nice to Have

~2 min read

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

This is an authentic Oscar Health job opportunity. Learn more about how you can safeguard yourself from recruitment fraud here.

At Oscar, being an Equal Opportunity Employer means more than upholding discrimination-free hiring practices. It means that we cultivate an environment where people can be their most authentic selves and find both belonging and support. We're on a mission to change health care -- an experience made whole by our unique backgrounds and perspectives.

Pay Transparency: Final offer amounts, within the base pay set forth above, are determined by factors including your relevant skills, education, and experience. Full-time employees are eligible for benefits including: medical, dental, and vision benefits, 11 paid holidays, paid sick time, paid parental leave, 401(k) plan participation, life and disability insurance, and paid wellness time and reimbursements.

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