Senior Data Scientist - Forecasting

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.

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.

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