Data Scientist, Oscar Health

• 3+ years of experience in data science, applied analytics, or a related quantitative field (industry, academia, or both)
• 2+ years of experience using SQL and Python and/or R to query, analyze, and manipulate data
• 2+ years of experience building data models, using more advanced analytics methods, statistical modeling, and/or data processing

Desirable

• As a Data Scientist II you will drive data science projects across multiple teams and domains
• In this role, you’ll take ownership of analytical and modeling work, contribute to technical direction, and partner closely with business, engineering, product and data stakeholders to deliver impactful solutions
• This is a mid-level role for data scientists who can operate independently, manage ambiguity, and apply advanced analytics or modeling techniques with minimal oversight
• ​​You will report into a leader on the Data team (Senior Data Scientist and above)
• This posting is representative of multiple roles, and final team placement will be determined during the interview process
• Work Location: This position is a hybrid role based in our New York City office, Los Angeles Office, or 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
• Research, develop, and maintain data pipelines, statistical models, and advanced analytical solutions
• Own projects end-to-end, including problem definition, implementation, validation, and iteration
• Deliver high-quality analytical and modeling outputs with limited manager oversight
• Collaborate closely with data science peers and cross-functional partners across business units
• Help ensure data science processes and outputs align with broader team strategies and roadmaps
• Provide guidance or informal mentorship to junior data scientists or analysts when needed
• Contribute to improving data science practices, tooling, and documentation