Director, Commercial AI & Advanced Analytics

Bristol Myers Squibb; Princeton (NJ); On-site; USD 168,000 - 203,000; Full time

Job summary

Bristol Myers Squibb in Princeton, NJ is seeking an Associate Director, Commercial AI and Advanced Analytics to lead advanced Marketing Mix (MMx), KDA, and causal analytics that inform brand investments and omnichannel strategy.

You will design, implement, and operationalize analytics pipelines, ensure model explainability, and partner with Brand, Omnichannel, and Finance teams across data sources to enable data-driven decision making.

Qualifications

• Advanced degree in a quantitative field.
• Minimum 5 years of pharma commercial analytics experience with MMx/MMM and causal analysis.
• Proven experience shaping brand strategy, budgets, and performance measures.
• Strong Python and/or R, SQL skills for modeling and data manipulation.
• Experience with cloud analytics platforms and production data pipelines.

Responsibilities

• Lead end-to-end development of MMx and KDA analyses to support brand planning and budget optimization.
• Apply advanced modeling techniques to quantify cross-channel incremental impact.
• Translate outputs into actionable business implications for brand strategy and investment.
• Build scalable MMx pipelines aligned with enterprise standards and automation.
• Partner with centralized teams to integrate MMx into analytics solutions and ensure explainability.

Skills

MMx analytics

Causal inference

Python

R

SQL

Data visualization

UAT testing

Problem solving

Education

Advanced degree in Statistics/ Economics/ Data Science/ OR

Tools

Databricks

Snowflake

Bayesian modeling

Job description

Bristol Myers Squibb in Princeton, NJ is seeking an Associate Director, Commercial AI and Advanced Analytics to lead advanced Marketing Mix (MMx), KDA, and causal analytics that inform brand investments and omnichannel strategy.

You will design, implement, and operationalize analytics pipelines, ensure model explainability, and partner with Brand, Omnichannel, and Finance teams across data sources to enable data-driven decision making.