Associate Director, Commercial AI & Advanced Analytics Princeton NJ

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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 handson and executionfocused 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 highquality ontime delivery of insights that directly impact brand strategy and ROI.

Responsibilities:

Deliver Advanced Marketing & Commercial Measurement

Own endtoend 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 inyear optimization and scenario analysis using MMx outputs.
Build & Operate Advanced MMx Capabilities

Design and run advanced MMx models using Bayesian Huber etc. approaches including:
Adstock and carryover modeling
Saturation and diminishing returns curves
Distributed lag and non-linear response functions
Crosschannel interaction effects
Develop scalable and repeatable MMx pipelines aligned with enterprise standards and automated platforms.
Partner with centralized teams to integrate MMx into selfservice and agentenabled analytics solutions.
Ensure models are explainable auditable and fit for use in a regulated pharmaceutical environment.
Agentic & AlwaysOn Insights Delivery

Contribute to the design and execution of agentic and alwayson insights capabilities that provide continuous decision support to Brand Omnichannel and Field teams.
Operationalize MMx KDA and causal models into alwayson analytics pipelines with defined refresh cadence data quality checks and monitoring.
Structure model outputs (drivers sensitivities scenarios constraints) to be consumable by AIenabled decision tools and agentbased workflows.
Support what changed / why and forwardlooking recommendation logic using causal and driverbased methods.
Ensure transparency lineage and explainability from data model insight recommendation with appropriate humanintheloop review.
Define and maintain the Key Business Questions (KBQ) framework and business context layer bridge business intent with the underlying technical semantic layer.
Partner with centralized platform engineering and Hyderabad teams to define inputs features and guardrails for agentenabled insights.
Design insights to be rolebased actionable and embedded into brand planning optimization and omnichannel execution workflows
Drive adoption of agentic AI tools through role-based training and structured feedback; serve as the primary business point of contact and channel user feedback into roadmap iteration.
Governance Compliance & Quality

Adhere 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 Partnership

Act as a trusted analytics partner to Brand Marketing Omnichannel Field and Finance teams.
Present insights in concise businessfirst narratives suitable for brand leadership and planning forums.
Support TA Analytics Leads by sharing best practices templates and modeling approaches.