• Build, optimize, and deploy scalable forecasting models that support pricing, promotions, and assortment strategies across multiple product categories • Apply advanced statistical, machine learning, and deep learning methods (e.g., ARIMA, Prophet, gradient boosting, LSTMs, hybrid ensembles) for forecasting at SKU, category, and chain levels • Implement robust MLOps practices for model deployment, monitoring, and retraining using cloud platforms (Azure, GCP, AWS) • Integrate multiple internal and external data sources (e.g., coupon redemption, merchandising, competitive, and macroeconomic data) into forecasting pipelines • Collaborate with data engineering to ensure scalable, high-quality data pipelines • Partner with business stakeholders in pricing, promotions, and assortment to design and validate forecast-driven decision workflows • Coach and mentor junior data scientists, sharing best practices in forecasting, MLOps, and applied analytics • Monitor forecast accuracy, perform backtesting, and refine models to reduce error rates and improve stability • Develop frameworks for scenario planning and simulation to measure business impact of promotions, pricing strategies, and assortment changes

• Solve complex problems, leverage large datasets, and build scalable and deployment ready models that work well with CVS Retail’s diverse product portfolio. • Guide the modeling approach, design and deploy end-to end solutions utilizing Operations Research (OR), econometric modeling, and forecasting along with the functional team leads • Partner with the Data Engineering team to architect scalable and fail-proof production pipelines, define the unified technical vision, and set standards • Stay up to date on the state-of-the-art modeling methodologies, initiate, lead, and inspire Research and Development efforts, define long-term technical vision and strategic roadmap • Act as a consultant who translates complex requirements and data science findings into decision ready narratives for cross-functional teams • Mandate and champion rigorous performance validation • Provide advanced technical mentorship, proactively identify critical organizational skill gaps, and standardize hiring processes.

• Design and develop user-facing analytic applications and dashboards in Palantir Foundry • Translate complex data models and analytics into clear, compelling visualizations • Build interactive, data-driven UIs that embed analytics and metrics into workflows • Collaborate with data scientists and engineers to integrate analytics, AI outputs, and ontologies • Apply UX/UI best practices to deliver accessible, intuitive, and scalable applications • Collaborate in an Agile/Scrum environment to rapidly iterate on solutions • Communicate insights effectively to technical and non-technical stakeholders

• Conduct data discovery and exploratory data analysis (EDA) across structured and unstructured data • Perform data cleansing, normalization, aggregation, and modeling • Design and build analytic applications in Palantir Foundry, including dashboards and interactive workflows • Apply advanced analytics and statistical methods (e.g., regression, clustering, hypothesis testing, A/B testing) • Develop and embed AI/ML capabilities (e.g., LLMs, NLP, RAG/GraphRAG) into analytic workflows • Create clear visualizations and metrics to support executive and operational decision-making • Collaborate in an Agile/Scrum environment to rapidly iterate on solutions • Communicate insights effectively to technical and non-technical stakeholders