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Senior Data Scientist - Risk Prediction Engine

CVS Health26,546 open roles

Where
NY - New York
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Hybrid
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Your applicationOpen nowSenior Data Scientist - Risk Prediction EngineCVS Health · NY - New York
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Share of postings closed within
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  2. 4.5%3 days
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  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: posted yesterday

The posting

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time.

Position Summary

Join our team of healthcare data scientists as we develop the next generation of risk prediction models. We're looking for data scientists to leverage their analytical & machine learning skills to help provide insights & model solutions to stakeholders across the CVS Health & Aetna organizations.

Our team routinely utilizes petabytes of data paired with extensive industry knowledge of actuarial partners to develop best-in-class machine learning models. We're looking to expand our team as we tackle more numerous & diverse use cases of the models we have been refining for nearly a decade now. You can help us overcome new challenges & build new solutions via the latest machine learning techniques. The team is looking for candidates with a passion for problem solving & quantitative analysis, strong algorithmic instincts, and the curiosity to learn new domains quickly and test ideas fast.

We are especially interested in candidates who embrace emerging technologies — including hands-on experience using AI tools to meaningfully increase their own productivity, and a working understanding of how large language models actually function — and who can thoughtfully incorporate AI into their data science processes to drive efficiency, insight, and innovation.

Overview:

  • Develops and/or uses algorithms and statistical predictive models and determines analytical approaches and modeling techniques to evaluate scenarios and potential future outcomes
  • Performs analyses of structured and unstructured data to solve multiple and/or complex business problems utilizing advanced statistical techniques and mathematical analyses and broad knowledge of the organization and/or industry
  • Collaborates with business partners to understand their problems and goals, develop predictive modeling, statistical analysis, data reports and performance metrics
  • Develops and participates in presentations and consultations to existing and prospective constituents on analytics results and solutions
  • Interacts with internal and external peers and managers to exchange complex information related to areas of specialization
  • Use strong knowledge in algorithms and predictive models to investigate problems, detect patterns and recommend solutions
  • Use strong programming skills to explore, examine and interpret large volumes of data in various forms
  • Applies sound risk management judgment when developing and validating models that inform business-critical decisions
  • Quickly ramps up on unfamiliar domains and methods, forming hypotheses and testing them efficiently to separate promising approaches from dead ends
  • Extensive experience with SQL, Python, Spark & Cloud computing (AWS, GCP, MS Azure)
  • Hands-on experience leveraging large language models and AI/ML ecosystem tools to deliver impactful products, with genuine fluency in how these models work under the hood

Required Qualifications

  • Bachelor's degree in Mathematics, Statistics, Computer Science, Business Analytics, Economics, Physics, Engineering, or related discipline
  • 3+ years of professional experience in data analytics, BI, data engineering or applied data science
  • 3+ years of experience with SQL and Python/R

Preferred Qualifications

  • Master's or PhD degree in Mathematics, Statistics, Computer Science, Business Analytics, Economics, Physics, Engineering, or related discipline
  • 5+ years of professional experience in data analytics, BI, data engineering or applied data science
  • 5+ years of experience with SQL and Python/R
  • Demonstrated track record of using AI tools to accelerate one's own workflow, paired with solid algorithmic and risk management acumen

Anticipated Weekly Hours

40

Time Type

Full time

Pay Range

The typical pay range for this role is:

$111,240.00 - $222,480.00

This pay range represents the base hourly rate or base annual full-time salary for all positions in the job grade within which this position falls. The actual base salary offer will depend on a variety of factors including experience, education, geography and other relevant factors. This position is eligible for a CVS Health bonus, commission or short-term incentive program in addition to the base pay range listed above.

Our people fuel our future. Our teams reflect the customers, patients, members and communities we serve and we are committed to fostering a workplace where every colleague feels valued and that they belong.

Great benefits for great people

We take pride in offering a comprehensive and competitive mix of pay and benefits that reflects our commitment to our colleagues and their families.

This full‑time position is eligible for a comprehensive benefits package designed to support the physical, emotional, and financial well‑being of colleagues and their families. The benefits for this position include medical, dental, and vision coverage, paid time off, retirement savings options, wellness programs, and other resources, based on eligibility.

Additional details about available benefits are provided during the application process and on Benefits Moments.

We anticipate the application window for this opening will close on: 11/22/2026

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws.

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