Senior Data Scientist Price Optimization Modeling

About the role

At CVS Health, we're building a world of health around every consumer and surrounding ourselves with dedicated colleagues who are passionate about transforming health care.As the nation's leading health solutions company, we reach millions of Americans through our local presence, digital channels and more than 300,000 purpose-driven colleagues - caring for people where, when and how they choose in a way that is uniquely more connected, more convenient and more compassionate. And we do it all with heart, each and every day. Position Summary The Consumer Engagement & Analytics team is helping lead the effort to drive improved consumer experience by partnering with key business areas across CVS Health to deliver impactful analytic products and insights. As a member of the Pricing Analytics team, you will be at the forefront of delivering high visibility products for key CVS Retail strategic priorities. S pecifically, you will have the opportunity to drive traffic, revenue and customer satisfaction in CVS Health's Front Store business using data science to optimize pricing decisions. In this role, you will have the opportunity to: Solve complex problems using operations research, dynamic programming, and reinforcement learning, translate business requirements into testable hypotheses and measurable metrics, build optimization models from the ground up 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 to assess model performance, Stay up to date on the state-of-the-art modeling methodologies and latest research, 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 i ncluding business partners, engineers, and other data and analytics teams . S hare 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, We are a fast-paced team focused on building innovative advanced analytics solutions using cloud capabilities. Within our team, we believe cutting-edge AI products and analytics can only be delivered if every aspect of the solution from data to model to front end UI is fully designed and developed by the team. We are looking for talented individuals who have a strong sense of ownership, accountability and a desire to deliver high quality end to end intuitive and impactful analytic products using advanced data driven approaches. Required Qualifications Bachelor's degree in a quantitative field such as Operations Research/Industrial Engineering, Applied Mathematics, Computer Science, Engineering or a related field. Master's degree is preferred. 3+ years of work experience in retail, consulting, or a related field, Demonstrated experience applying operations research, reinforcement learning, and/or dynamic programming techniques, Strong Python, R, and SQL skills, proficiency in working with large datasets, Hands on experience solving pricing, promotions, assortment, or supply chain problems by building mathematical optimization models using open-source or commercial optimization solvers (such as Pyomo, Gurobi, Pulp, ILOG CPLEX), 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.), Excellent communication and presentation skills and attention to detail. Worked in an agile environment, has the flexibility to adapt to changing business needs, Ability to communicate technical concepts to non-technical audiences, including experience creating communication materials (e.g., white paper, slide decks, etc.). Preferred Qualifications PhD in Operations Research, Management Science or equivalent, 5+ years of work experience in retail, consulting, or a related field, Experience developing price optimization models, in depth understanding of merchandising (price, promotion, assortment) concepts and metrics in retail, Experience with managing large scale projects and working with multiple business stakeholders. Education Bachelor's degree in a quantitative field such as Operations Research/Industrial Engineering, Applied Mathematics, Computer Science, Engineering or a related field. Master's deg

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