Senior Data Scientist

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:

We are a Data Science team at Oscar dedicated to improving the Member Experience by embedding advanced analytics into our core technology and operations. We focus on building data products that bridge the gap between complex health insurance workflows and seamless, member-centric service.

You will drive the evolution of our member-facing tools by developing the LLM frameworks and ML models that underpin our automated support systems and digital interfaces. You will be responsible for evaluating both tool performance and member behavior to surface deep insights that inform our broader product and operations strategy.

You will report into the Lead Data Scientist.

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:

• Works with team and manager to impact longer term strategies and roadmap
• Sets shorter term roadmap for team
• May manage data scientists and/or analysts
• Interacts and collaborates closely with data and business counterparts across functional areas
• Researches, develops, and maintains data pipelines, statistical/ML models, and/or advanced analyses
• 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, 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
• Experience evaluating consumer-facing digital products in collaboration with Product and Engineering teams

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.

Artificial Intelligence (AI): Our AI Guidelines outline the acceptable use of artificial intelligence for candidates and detail how we use AI to support our recruiting efforts.

Reasonable Accommodation: Oscar applicants are considered solely based on their qualifications, without regard to applicant's disability or need for accommodation. Any Oscar applicant who requires reasonable accommodations during the application process should contact the Oscar Benefits Team (View email address on click.appcast.io) to make the need for an accommodation known.

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