Associate Director, Commercial AI and Advanced Analytics

Working with UsChallenging. Meaningful. Life-changing. Those aren’t words that are usually associated with a job. But working at Bristol Myers Squibb is anything but usual. Here, uniquely interesting work happens every day, in every department. From optimizing a production line to the latest breakthroughs in cell therapy, this is work that transforms the lives of patients, and the careers of those who do it. You’ll get the chance to grow and thrive through opportunities uncommon in scale and scope, alongside high-achieving teams. Take your career farther than you thought possible.Bristol Myers Squibb recognizes the importance of balance and flexibility in our work environment. We offer a wide variety of competitive benefits, services and programs that provide our employees with the resources to pursue their goals, both at work and in their personal lives. Read more: careers.bms.com/working-with-us.Summary:The Associate Director, Commercial AI and Advanced Analytics is responsible for delivering advanced commercial measurement and decision intelligence across BMS brands and therapeutic areas. This role owns the design, execution, and operationalization of advanced Marketing Mix (MMx), causal, and optimization analytics that inform investment decisions, omnichannel strategy, and performance optimization.This position is highly hands‑on and execution‑focused, combining strong technical depth in marketing analytics with the ability to translate complex modeling outputs into clear, actionable recommendations for Marketing, Brand, Omnichannel, Field, and Finance partners. The Associate Director operates within an enterprise analytics framework, aligning with TA Analytics Leads and centralized platforms while ensuring high‑quality, on‑time delivery of insights that directly impact brand strategy and ROI.Responsibilities:Deliver Advanced Marketing & Commercial MeasurementOwn end‑to‑end development and execution of advanced Marketing Mix (MMx) and Key Driver Analyses (KDA) to support brand planning, budget optimization, and performance assessment.Apply advanced modeling techniques to quantify incremental impact across channels (sales force, digital, TV, congresses, patient programs).Translate modeling outputs into clear business implications for brand strategy, media mix, and investment allocation.Support annual brand planning, in‑year optimization, and scenario analysis using MMx outputs.Build & Operate Advanced MMx CapabilitiesDesign and run advanced MMx models using Bayesian, Huber, etc. approaches, including:Adstock and carryover modelingSaturation and diminishing returns curvesDistributed lag and non-linear response functionsCross‑channel interaction effectsDevelop scalable and repeatable MMx pipelines aligned with enterprise standards and automated platforms.Partner with centralized teams to integrate MMx into self‑service and agent‑enabled analytics solutions.Ensure models are explainable, auditable, and fit for use in a regulated pharmaceutical environment.Agentic & Always‑On Insights DeliveryContribute to the design and execution of agentic and always‑on insights capabilities that provide continuous decision support to Brand, Omnichannel, and Field teams.Operationalize MMx, KDA, and causal models into always‑on analytics pipelines with defined refresh cadence, data quality checks, and monitoring.Structure model outputs (drivers, sensitivities, scenarios, constraints) to be consumable by AI‑enabled decision tools and agent‑based workflows.Support “what changed / why” and forward‑looking recommendation logic using causal and driver‑based methods.Ensure transparency, lineage, and explainability from data → model → insight → recommendation, with appropriate human‑in‑the‑loop review.Partner with centralized platform, engineering, and Hyderabad teams to define inputs, features, and guardrails for agent‑enabled insights.Design insights to be role‑based, actionable, and embedded into brand planning, optimization, and omnichannel execution workflows.Governance, Compliance & QualityAdhere to data privacy, AI governance, and model validation standards (HIPAA, GDPR/CCPA, internal AI controls).Maintain clear documentation of assumptions, methods, and limitations.Participate in model reviews and audits with Legal, Privacy, and Governance stakeholders.Stakeholder PartnershipAct as a trusted analytics partner to Brand, Marketing, Omnichannel, Field, and Finance teams.Present insights in concise, business‑first narratives suitable for brand leadership and planning forums.Support TA Analytics Leads by sharing best practices, templates, and modeling approaches.Qualifications:Advanced degree in Statistics, Economics, Data Science, Operations Research, or a related quantitative field.Minimum 5 years of experience in pharmaceutical commercial analytics, with direct ownership of MMx / MMM and causal analysis.Proven experience supporting brand strategy, budget planning, and performance measurementsHands‑on expertise in advanced Marketing Mix Modeling, including:Bayesian and hierarchical modeling frameworksAdstock, lag, and saturation modelingNon‑linear optimization and scenario simulationStrong background in causal inference and incrementality measurement, such as:Geo‑experiments and matched‑market testsSynthetic control methodsUplift / incremental response modelingProficiency in Python and/or R for statistical modeling, feature engineering, and automation.Solid SQL skills and experience working with large, multi‑source pharma datasets.Experience with cloud analytics platforms (e.g., Databricks, Snowflake) and production data pipelines.Familiarity with MLOps, version control, and model lifecycle management.Strong understanding of pharma commercial data (claims, APLD, specialty pharmacy, promotional, and digital engagement data).Experience integrating analytics with BI tools and decision workflows.Exposure to AI‑enabled or automated analytics platforms is a plus (agentic systems not required but beneficial).Abil