Senior Manager, Category Promotion & Coupon Analytics

CVS Health•Woonsocket, RI

About The Position

The Senior Manager, Category Promo & Coupon Analytics will lead the development of data-driven promotional and pricing strategies that drive customer engagement, sales, and margin. This role sits within the Price and Value organization and partners cross-functionally with Merchandising, Marketing, and Analytics teams to uncover insights, optimize discount strategies, and translate analytics into actionable business plans. This is a highly analytical and technical role requiring expertise in large-scale data analysis, advanced programming, and modern data platforms to inform strategic decision-making.

Requirements

Bachelor’s degree required
7+ years of experience in analytics, strategy, pricing, promotions, or related fields
Strong proficiency in SQL and Python for data analysis and modeling
Experience working with modern data platforms (e.g., Databricks, Snowflake, or similar )
Proven ability to analyze large datasets and translate insights into business impact
Strong financial acumen and experience managing or influencing performance metrics
Excellent communication skills with the ability to influence cross-functional stakeholders

Nice To Haves

Master’s degree (MBA, MS in Analytics, Data Science, or related field)
Experience with Palantir Foundry or similar advanced analytics platforms
Experience in retail, pricing, promotions, loyalty, or consumer-focused industries
Experience building and scaling data products, dashboards, or advanced analytics solutions
Familiarity with experimentation frameworks and advanced statistical methods

Responsibilities

Develop and execute data-driven pricing, promotion, and coupon strategies that maximize sales, margin, and customer value
Analyze large, complex datasets to identify trends, risks, and opportunities across categories
Translate analytical insights into clear, actionable recommendations for senior leadership
Design and evaluate tests (A/B, pilots) to measure effectiveness of promotional strategies
Leverage SQL, Python, and modern data platforms to extract, transform, and analyze data at scale
Build scalable analytical models, forecasting tools, and reporting dashboards
Utilize platforms such as Databricks, Snowflake, and/or Palantir Foundry to integrate and analyze enterprise data
Partner with data engineering and analytics teams to enhance data pipelines and capabilities
Size opportunities and forecast impact of promotional initiatives
Monitor performance against key KPIs (sales, margin, ROI) and adjust strategies accordingly
Support annual planning, budgeting, and ongoing financial tracking
Collaborate with Merchandising, Marketing, Loyalty, and Operations to align strategies with business goals
Influence stakeholders through data-driven storytelling and executive-level presentations
Act as a thought leader in promotional and pricing strategy discussions
Identify opportunities to improve efficiency, automation, and analytical capabilities
Stay current on industry trends, tools, and best practices in pricing, promotions, and retail analytics
Drive adoption of new technologies and advanced analytic approaches