Data Scientist - Pricing and Promotions Optimization

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

The Retail Analytics team is helping lead the effort to transform healthcare and drive improved consumer experience by partnering with key business areas across CVS Health and delivering impactful analytic solutions and insights. As a member of this team, you will be at the forefront of delivering high visibility projects for key CVS Retail strategic initiatives. Specifically, you will have the opportunity to drive revenue and customer satisfaction in CVS Health’s Front Store business using data science to optimize pricing and promotions decisions. You will work cross functionally with both technical and non-technical stakeholders and translate their business needs into problems to be solved using statistical modeling, machine learning, and optimization. We are a fast-paced team focused on building innovative advanced analytics solutions using cloud capabilities. We are looking for individuals who have a strong sense of ownership, accountability, and a desire to deliver high quality and high impact products using advanced data driven approaches. Key responsibilities and what you will do:

• Algorithm Development: Develop, validate, and deploy scalable optimization algorithms to achieve business objectives and inform strategic decision-making across CVS Health’s retail business. Define and monitor model performance metrics, ensuring alignment with business impact over time. Develop proof of concepts and transition solutions into production-ready pipelines and APIs as required by the business. 

• Cross-Functional Collaboration: Collaborate with product managers, data engineering, software engineering, and data science teams to identify and implement impactful solutions to solve complex business problems, fostering trust and commitment through agile methodologies. 

• Data Exploration: Analyze and interpret large volumes of structured and unstructured data to address complex business challenges effectively. Develop and maintain datasets and pipelines to organize, collect, and standardize data, facilitating insights and addressing reporting needs. 

• Continuous Learning: Stay abreast of the latest advancements in optimization algorithms, machine learning solutions, and methodologies to enhance capabilities. Research and integrate new technologies to enhance existing solutions and address emerging challenges. 

Required Qualifications

• 1+ years of demonstrated experience applying operations research, reinforcement learning, and/or dynamic programming techniques. 

• 1+ years of experience building linear and nonlinear programming models for mathematical optimization and experience with optimization tools and libraries (Gurobi, Pulp, Pyomo, CPLEX). 

• 1+ years of experience in SQL and Python programming. 

• Experience working with large datasets, analyzing data, and extracti