Senior Data Scientist, Data & Member Behavior (Campaign Builder)

Hi, we're Oscar. We're hiring a Senior Data Scientist to join our Engineering team.

Oscar is the first health insurance company built around a full stack technology platform and a 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

Oscar is in a unique position to drive impact through high engagement with members and a variety of high-tech touchpoints (such as virtual care or superagent).The Senior Data Scientist develops personalized multi-channel marketing campaigns to influence behaviors that Oscar members take that are key to their health. You will ideate, scope business cases, design targeted pipelines by using predictive models, launch campaigns, monitor and optimize campaigns in real time to attribute best performing marketing variants, and measure campaigns. This will involve research, pipeline/ML model development, optimization techniques such (e.g. MAB), and measurement techniques (traditional statistical and casual machine learning).

You work cross functionally with marketing and clinical teams, dedicated to a specific goal of lowering medical cost. You will have accountability for the success of each campaign.

You will report to the Senior Director, Data Science.

Work Location:

Oscar is a blended work culture where everyone, regardless of work type or location, feels connected to their teammates, our culture and our mission.

This is a hybrid role in our New York office. You will work part of the time in the office and part of the time remote / work-from-home. #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

• Works with team and manager to impact longer term strategies and roadmap


• Sets shorter term roadmap for team


• 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

Qualifications

• 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

Travel

Up to 5%

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.

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.

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