Associate Director, Commercial AI & Advanced Analytics - Princeton NJ

Job Description

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Unless specifically stated otherwise, this role is "On-Site" at the location detailed in the job post.

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 Measurement

Own 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 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
Cross-channel interaction effects
Develop 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 Delivery

Contribute 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.
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 agent-enabled insights.
Design insights to be role-based, 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…