Director, US Commercial AI & Advanced Analytics

About the role

The Director, US Commercial AI & Advanced Analytics is accountable for driving advanced marketing mix and commercial decision intelligence across BMS, with a strong focus on translating marketing investments into measurable business impact.

This role leads the design, build, and operationalization of Marketing Mix (MMx), Key Driver, and optimization capabilities that inform investment planning, channel strategy, and performance optimization across brands and therapeutic areas.

This position combines innovation with disciplined execution, modernizing marketing and commercial measurement through scalable, AI-enabled decision platforms.

Responsibilities

• Drive Marketing & Commercial Decision Support
• AI-driven measurement, scenario planning, and optimization to support brand strategy, portfolio decisions, and launches
• Support automation of Marketing Mix, Key Driver Analyses (KDA), and budget optimization to reduce cycle time and manual effort
• Architect and deploy Agentic AI solutions—including autonomous insight agents, multi-step reasoning workflows, and LLM-powered decision tools—that proactively surface commercial insights and reduce analyst dependency
• Partner with BI&T and global delivery teams to leverage analytics-ready datasets (ARDs) and standardized data products
• Modernize Brand & Omnichannel Insights
• Contribute to the deployment and enhancement of agentic MMx and advanced analytics platforms supporting Brand Analytics, TA teams, and Omnichannel stakeholders
• Ensure analytics outputs are integrated into annual planning, investment decisions, and media strategy discussions
• Support always-on insights capabilities that deliver role-based, actionable intelligence across Marketing, Field, and Medical teams
• Apply experimentation and causal inference approaches (A/B tests, incrementality, econometric models) to quantify impact and optimize spend
• Enable TA-Aligned Teams & Global Delivery
• Manage and develop a team of analytics professionals or technical leads
• Translate complex analytics into clear, business-focused insights and recommendations for brand and functional leaders
• Represent Commercial Analytics & AI in cross-functional project teams and working forums

Qualifications

• Advanced degree in Data Science, Statistics, Computer Science, Economics, or related field
• Minimum 8 years of experience in pharmaceutical commercial analytics, decision science, or related roles, with hands-on experience in MMM/MMx, KDA, and resource optimization
• 3+ years of experience leading analytics teams or significant cross-functional initiatives
• Strong expertise in causal inference and incrementality measurement (e.g., geo-experiments, matched-market tests, uplift modeling)
• Demonstrated experience designing and deploying Agentic AI systems—including multi-agent orchestration, LLM-based reasoning pipelines, tool-use frameworks, and autonomous workflow automation in a pharma or life sciences commercial context
• Experience implementing ML model lifecycle management (MLOps)—covering model training, validation, deployment, monitoring, drift detection, and retraining—within cloud-based production environments
• Proficiency in Bayesian, hierarchical, and econometric MMx techniques (adstock, lag, saturation) and their application to budget and channel optimization
• Experience with agentic AI concepts, LLMs, RAG, and scalable analytics platforms (hands-on experience a plus)
• Experience operationalizing analytics or AI solutions into business workflows and driving adoption
• Familiarity with pharma data assets (claims, APLD, specialty pharmacy, promotional, digital)
• Understanding of analytics and AI governance in regulated environments (privacy, risk, compliance)
• Practical knowledge of responsible AI practices for Agentic systems, including agent guardrails, prompt engineering governance, output auditing, and explainability in regulated pharma environments
• Experience with cloud analytics platforms (e.g., Databricks, Snowflake) and BI tools
• Working knowledge of data privacy requirements (HIPAA, GDPR/CCPA)