Lead Data Scientist

Hi, we're Oscar. We're hiring a Lead 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 Lead Data Scientist, Claims will drive modeling and analytics for the core of our technology – our claims payment system. In this role, you will:

• Partner with operations and technology leaders in the design and implementation of initiatives to improve claims system performance


• Use sophisticated measurement and data mining techniques to drive deep and rapid insights


• Use data to achieve our goal of being the most automated and efficient insurer in the industry

You will report into the Senior Director, Data Science.

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. #LI-Hybrid

Pay Transparency: The base pay for this role is: $174,400 - $228,900 per year. You are also eligible for employee benefits, company equity grants, and annual performance bonuses.

Responsibilities:

• Translates business goals into plans and tactics for the team


• Works with more senior leaders to establish longer term strategies and roadmaps


• Participates in team-wide technical and operations management responsibilities


• Interacts and collaborates closely with data and business management across functional areas


• Leads the research, development, and maintenance of data pipelines, statistical/ML models, and/or advanced analyses


• Compliance with all applicable laws and regulations


• Other duties as assigned

Requirements:

• 6+ years of industry or other quantitative technical fields (which may include academia)


• 4+ years of work experience working with SQL, R, and/or Python to query, manipulate and analyze data


• 4+ 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

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 ([email protected]) to make the need for an accommodation known.

California Residents: For information about our collection, use, and disclosure of applicants’ personal information as well as applicants’ rights over their personal information, please see our .