Associate Director, Commercial AI Product Owner

Job description

Working with Us Challenging. 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 Product Owner is responsible for leading the transformation of advanced analytics into durable, scalable, and AI-powered solutions that directly accelerate commercial decision-making across the enterprise. You will collaborate across global teams—including BI&T, Data Science, and the engineering/analytics group—to deliver high-quality, production-grade analytics platforms, tools, and automation that embed actionable intelligence into everyday workflows for Marketing, Field, and Market Access stakeholders. This role enables the shift from project-based analytics to platform-enabled, always-on decision intelligence. You will operate within a hub-and-spoke model, setting standards, governance, and reusable components that empower therapeutic area-aligned teams while driving enterprise-wide consistency, speed, and reliability. You’ll be a technical and strategic leader, guiding cross-functional pods, productizing analytical models, and driving innovation within agentic AI platforms to support forward-looking, actionable brand and omnichannel insights. Responsibilities: Tools, Automation, & AI Products Product Ownership: Serve as dedicated product owner for the Agentic MMx (Marketing Mix) Platform - own its strategy, vision, roadmap, and stakeholder alignment in partnership with BI&T and Data Science. Drive the ongoing evolution of this self-service analytics hub to deliver advanced capabilities, including KDA, scenario simulation, investment planning, constrained optimization, and real-time decision support. Pod Leadership: Lead the Tools & Automated Solutions cross functional team across BI&T, Data Science, TA Analytics, and analytics/engineering to architect, launch, and maintain scalable analytics solutions—covering dashboards, always-on insights, scenario simulators, measurement pipelines, and democratized KDA platforms. Collaboration: Partner with BI&T, Data Science, TA Analytics, and engineering to deliver analytics-ready datasets, feature stores, semantic layers, and automated data pipelines, standardizing and accelerating insight generation. Efficiency and Innovation: Champion automation, templated workflows, and platformization to reduce manual effort and external vendor reliance, maximizing reuse and operational efficiency. Continuously identify opportunities for tool innovation and scalable enablement of best practice measurement solutions. Integrate decision science outputs into annual planning, CRM (e.g., Veeva), and omnichannel orchestration workflows via APIs and embedded dashboards to ensure sustained adoption and business impact. Develop monitoring and governance dashboards for real-time oversight of model/data health, user adoption, SLAs, drift/stability, and auditability. Agentic & AI Capability Development Architect and deploy autonomous and semi-autonomous analytics agents using multi-agent frameworks, enabling progression from descriptive analytics to causal analysis, root-cause insights, and predictive recommendations. Own the AI product lifecycle: manage proof-of-concept, pilot, rollout, and continuous optimization; establish robust governance covering safety, security, ethical standards, and privacy compliance. Cross-Functional Team Management & Enablement Lead cross-functional pods (BI&T engineers, analytics/data engineers, platform SMEs), managing product roadmaps, agile backlogs, and release cycles. Codify and promote engineering standards for deployment, MLOps, CI/CD, QA/testing, SLAs/SLOs, and RACI matrices for reliability and quality. Standardize and scale processes, maximize component reuse, minimize vendor dependence, and ensure governance and privacy compliance. Coach and enable enterprise and TA-aligned analytics teams, driving best practice adoption, technical enablement, and a culture of consistent delivery and innovation. Promote agile ways of working using collaboration platforms (e.g., Jira) for rapid development and communication. Advance Governance, Compliance & Trust Partner with Data Governance, Legal, and Privacy teams to define and enforce data/AI governance: SLAs, RACI, privacy-by-design, and responsible/ethical AI controls. Ensure AI tools and solutions are explainable, auditable, and compliant; continuously monitor for bias, document decisions, and incorporate human-in-the-loop mechanisms where required. Lead structured change management and feedback loops to drive sustained tool adoption and measurable business outcomes. Qualifications: Advanced degree (MS/PhD preferred) in Data Science, Statistics, Computer Science, Econometrics, or related quantitative field. Minimum 5 years of hands-on experience in pharma commercial analytics or decision science. Proficiency with causal inference and incrementality tools (geo-experiments, matched markets, synthetic controls, uplift modeling). Expertise in Bayesian/hierarchical MMx, adstock/distributed lag, saturation/response curve modeling, and operationalizing these methodologies in automated pipelines and platforms. Proven experience launching and scaling agentic AI solutions (multi-agent systems, LLMs, RAG, semantic layers, real-time architectures). Deep proficiency in enabling agent collaboration, negotiation, and task orchestration, including coordination of agent roles/functions within a commercial analytics or decision science context. Proven experience operationalizing LLMs for commercial use cases—knowledge retrieval, summarization, generative analytics, automation of insight generation, Experience embedding AI analytics platforms into commercial workflows with enterprise-wide adoption. Extensive knowledge of pharmaceutical data (claims, APLD, specialty pharmacy, digital signals, promotional data). Strong foundation in AI governance (risk management, security, privacy, model monitoring, human-in-the-loop) in regulated environments. Experience with cloud analytics platforms (Databricks, Snowflake, Spark), MLOps, and BI tools; understanding of HIPAA, GDPR/CCPA and regulatory standards. Mastery of programming and data science tools (Python, R), machine learning frameworks (scikit-learn, PyTorch), large-scale analytics environments, visualization platforms, and workflow automation. Familiarity with CRM (e.g., Veeva), omnichannel metrics, multi-touch attribution (MTA), and AI-driven next-best-action frameworks. Outstanding stakeholder engagement and communication skills—capable of translating complex analytics concepts into actionable business strategies. #CASA If you come across a role that intrigues you but doesn’t perfectly line up with your resume, we encourage you to apply anyway. You could be one step away from work that will transform your life and career. Compensation Overview: Princeton - NJ - US: $167,540 - $203,013 The starting compensation range(s) for this role are listed above for a full-time employee (FTE) basis. Additional incentive cash and stock opportunities (based on eligibility) may be available. The starting pay rate takes into account characteristics o