Data Scientist - Pricing and Promotions Optimization

CVS Health•New York, NY

20h•Onsite

About The Position

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.

Requirements

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 extracting meaningful insights.
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.).
Experience using applied statistics and machine learning techniques.
Proven experience in analyzing complex problems and translating them into efficient data science algorithms with a focus on computational efficiency.

Nice To Haves

A strong drive to explore data and make a business impact by applying data science and the curiosity to dive deep.
Excellent communication and presentation skills and attention to detail.
PhD in Operations Research, Management Science or equivalent.
Retail domain knowledge and basic understanding of pricing and promotions concepts.
Experience using PySpark and/or big data platforms (e.g., Hadoop, Spark) for large data processing.
Knowledge of or experience in causal inference, and machine learning algorithms.
Ability to effectively communicate technical concepts to non-technical audiences, including experience creating communication materials (e.g., white paper, slide decks, etc.).

Responsibilities

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.
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.
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.
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.