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
- Solve complex problems, translate business requirements into testable hypotheses and measurable metrics, build predictive models to understand localized trends, assess the competitive environment, and measure short- and long- term customer impacts to optimize pricing decisions,
- Develop and leverage in-depth knowledge of Retail Merchandising business processes, translate key drivers of business value to analytics opportunities, and simulate impact of business decisions to improve customer experience,
- Guide the technical approach, leverage large datasets, and build scalable and deployment ready models that work well with CVS Retail’s diverse product portfolio, develop robust methodologies and metrics to assess model performance,
- Stay up to date on the state-of-the-art modeling methodologies and latest research,
- Implement scalable high-performance computing techniques to speed up forecasting models
- Utilize the latest developments in the generative models (LLMs and other AI models) to improve and enrich the performance of the pricing models, rethink the deployment readiness and scalability of the models, and automation opportunities using agents,
- Work cross functionally with a range of technical and non-technical stakeholders including business partners, engineers, and other data and analytics teams. Share progress, findings, recommendations, and their business implications. Present meaningful and insights-driven materials on analytical results with recommendations and go forward planning to guide a variety of audiences including internal stakeholders and senior leadership.
Required Qualifications
- Bachelor’s degree in a quantitative field such as statistics, engineering, or a related field. Master’s degree is preferred
- 3+ years of work experience as a Data Scientist in retail, consulting, or a related field
- Demonstrated experience building and scaling forecasting models in a production environment, for a diverse portfolio of products (seasonal, non-seasonal, new, mature, end of life) and lead times
- Hands on experience with statistical, machine learning and deep learning-based forecasting techniques, hyper-parameter tuning, and ensembles to forecast at short and long horizons
- Strong Python and SQL skills, proficiency in working with large datasets
- Experience working with a data engineering/MLOps team to productionize data science models, familiarity with version control (GitLab or GitHub), and ML platforms (AWS SageMaker, Databricks, GCP Vertex AI, etc.)
- Willingness to learn and willingness to coach
- Excellent communication and presentation skills and attention to detail. Worked in an agile environment, has the flexibility to adapt to changing business needs
Preferred Qualifications
- PhD in a quantitative field such as mathematics, engineering, physics or equivalent
- Publicly available git-repo with code samples of work
- Experience writing modular, production ready code
- 5+ years of work experience as a Data Scientist or Senior Data Scientist in retail, consulting, or a related field
- Comfortable with best practices in asynchronous communication
- Demonstrated experience with high performance computing methods
- In depth understanding of merchandising (price, promotion, assortment) concepts and metrics in retail, experience working on a team with a focus on supply chain, inventory management, or merchandising
- E-Commerce experience is desired but not required
- Experience working with multiple business stakeholders
Education
- Bachelor’s degree in a quantitative field such as statistics, engineering, or a related field. Master degree/PhD preferred.
Anticipated Weekly Hours
40Time Type
Full timePay Range
The typical pay range for this role is:
$101,970.00 - $203,940.00This 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.
Additional details about available benefits are provided during the application process and on Benefits Moments.
Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws.
Skills Required
- Bachelor's degree in statistics, engineering, or a related quantitative field
- 3+ years of experience as a Data Scientist in retail, consulting, or a related field
- Experience building and scaling forecasting models in a production environment across diverse product portfolios and lead times
- Hands-on experience with statistical, machine learning, and deep learning forecasting techniques, hyperparameter tuning, and ensembles
- Strong Python and SQL skills, with experience working with large datasets
- Experience working with data engineering or MLOps teams to productionize data science models
- Familiarity with version control such as GitLab or GitHub
- Familiarity with ML platforms such as AWS SageMaker, Databricks, or GCP Vertex AI
- Willingness to learn and coach others
- Excellent communication and presentation skills
- Attention to detail and experience working in an agile environment
- Flexibility to adapt to changing business needs
- Master's degree in a quantitative field
- PhD in mathematics, engineering, physics, or an equivalent quantitative field
- Publicly available Git repository with work samples
- Experience writing modular, production-ready code
- 5+ years of experience as a Data Scientist or Senior Data Scientist
- Experience with asynchronous communication best practices
- Experience with high-performance computing methods
- Knowledge of retail merchandising concepts and metrics, including price, promotion, and assortment
- Experience with supply chain, inventory management, or merchandising teams
- E-commerce experience
- Experience working with multiple business stakeholders
CVS Health Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about CVS Health and has not been reviewed or approved by CVS Health.
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Healthcare Strength — Health coverage includes medical, dental, and vision with HSA-eligible options, free preventive care, virtual care, and access to MinuteClinic services. Mental-health resources such as counseling support are emphasized, and coverage is often considered solid for full-time colleagues.
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Retirement Support — A dollar-for-dollar 401(k) match up to 5% after one year and an Employee Stock Purchase Plan are consistently highlighted in Total Rewards materials. Feedback suggests retirement programs are a meaningful strength within the overall package.
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Wellbeing & Lifestyle Benefits — Wellbeing offerings include up to 20 no-cost counseling sessions per issue, backup care, tuition assistance, and substantial in-store discounts, alongside broader wellness tools. These everyday perks expand value beyond base pay and can be especially meaningful for full-time schedules.
CVS Health Insights
What We Do
CVS Health is the leading health solutions company that delivers care in ways no one else can. We reach people in more ways and improve the health of communities across America through our local presence, digital channels and our nearly 300,000 dedicated colleagues – including more than 40,000 physicians, pharmacists, nurses and nurse practitioners. Wherever and whenever people need us, we help them with their health – whether that’s managing chronic diseases, staying compliant with their medications, or accessing affordable health and wellness services in the most convenient ways. We help people navigate the health care system – and their personal health care – by improving access, lowering costs and being a trusted partner for every meaningful moment of health. And we do it all with heart, each and every day.
