Manager, Commercial AI Product Owner

Bristol-Myers Squibb Co; Hyderabad; On-site; INR 3,000,000 - 4,200,000; Full time

Job summary

Bristol Myers Squibb Co. seeks a senior analytics product owner to lead the MMx and AOI platforms, shaping strategy, roadmap, and stakeholder alignment.

You will drive self‑service analytics, integrate outputs into planning and CRM workflows, and monitor dashboards for health, adoption, and value realization. Collaborating with BI&T, Data Science, and engineering, you will accelerate automation, governance, and scalable analytics while ensuring compliance and user-centric design.

Qualifications

• Advanced degree preferred in data science or related quantitative field.
• 7+ years in pharma analytics or decision science with production AI solutions.
• Experience mentoring analytics talent and leading cross-functional pods.
• Hands-on with multi-agent AI, LLMs, and enterprise analytics workflows.

Responsibilities

• Product co-owner for MMx and AOI platforms; define strategy, vision and roadmap.
• Integrate decision-science outputs into annual planning and omnichannel workflows.
• Build analytics-ready datasets, feature stores, and automated pipelines.
• Monitor dashboards for model health, SLAs, drift, and auditability.
• Partner across BI&T, Data Science, TA Analytics, and engineering teams.

Skills

Stakeholder engagement

Project management

Analytical problem solving

Strategic mindset

Education

MS/PhD in Data Science or quantitative field

BA/BS in a quantitative field with strong experience

Tools

Python

R

scikit-learn

PyTorch

Databricks / Spark

BI tools

Job description

At Bristol Myers Squibb, our employees often ask, “Who are you working for?”—a question that fuels collaboration, accountability, and urgency in our work. Our purpose-driven culture inspires us to discover, develop, and deliver innovative medicines to prevail over serious diseases. We offer uniquely interesting and meaningful work, opportunities for growth, and a supportive environment that values inclusion, wellbeing, flexibility, and comprehensive benefits. This is work that transforms the lives of patients, and the careers of those who do it.

Roles & Responsibilities

Analytics Delivery, Tools & AI Products

Product co-ownership: Serve as dedicated product co-owner for the Agentic MMx (Marketing Mix) and Always on Insights (AOI) Platform – partner on its strategy, vision, roadmap, and stakeholder alignment in collaboration with BI&T and Data Science. Drive the ongoing evolution of this self-service analytics hub to deliver advanced capabilities, including MMx, scenario simulation, investment planning, constrained optimization, and real-time decision support. Workflow integration: Partner with BI&T to 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. Monitoring & oversight: Support monitoring and governance dashboards for real-time oversight of model/data health, user adoption, SLAs, drift/stability, and auditability. 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 platform creation 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. Product KPIs & enablement: Define and track product KPIs—adoption, activation, retention, and model accuracy vs. business lift—and build training content, enablement, and adoption playbooks to drive sustained usage and value realization.

Agentic & AI Capability Development

Support the design and deployment of autonomous and semi-autonomous analytics agents using multi-agent frameworks, enabling progression from descriptive analytics to causal analysis, root-cause insights, and predictive recommendations. Contribute to the AI product lifecycle—proof-of-concept, pilot, rollout, and continuous optimization—while helping establish governance covering safety, security, ethical standards, and privacy compliance. Operationalize LLMs for commercial use cases such as knowledge retrieval, summarization, generative analytics, and automation of insight generation.

Stakeholder Partnership & Strategic Support

Partner closely with US Commercial stakeholders, Global Analytics, OCx, Marketing, UX/Design, and BI&T to understand business needs, scope analytical solutions, and design impactful deliverables. Act as a strategic thought partner—helping stakeholders frame decisions, interpret insights, and understand trade-offs and implications. Articulate ROI and business cases to guide AI investment, prioritization, and resource-allocation decisions—quantifying expected business lift against cost, effort, and risk. Collaborate closely with UX/Design to shape intuitive, user-centered product experiences that maximize adoption, ease of use, and stakeholder trust. Manage and prioritize competing business demands across time zones to ensure alignment with strategic objectives and effective demand management for the Hyderabad hub.

Technical Oversight, Governance, Compliance & Trust

Oversee all technical tasks performed by the analytics team, including dashboards, business rules, documentation, automated pipelines, and model governance. Coordinate with BI&T teams to ensure reliable, timely, and scalable data flows into downstream analytics and reporting solutions. Partner with Data Governance, Legal, and Privacy teams to apply data/AI governance: SLAs, RACI, privacy-by-design, and responsible/ethical AI controls. Ensure analytical outputs are well-documented, reproducible, explainable, auditable, and compliant—monitoring for bias and incorporating human-in-the-loop mechanisms where required.

Required Qualifications

Education & Experience Advanced degree (MS/PhD) preferred in Data Science, Statistics, Computer Science, Econometrics, or a related quantitative field; a BA/BS with strong relevant experience will be considered. 7+ years of hands-on experience in pharma commercial analytics or decision science, including experience developing and shipping production-grade AI led analytical solutions. Experience managing, mentoring, and developing analytics talent, and leading cross-functional pods in a global enterprise environment. Hands‑on experience building and scaling agentic AI solutions (multi‑agent systems, LLMs, RAG, semantic layers, real‑time architectures). 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). Product management/product owner (PM/PO) certification (e.g., CSPO, SAFe PO/PM, Pragmatic Institute) a plus.

Core Competencies

• Outstanding stakeholder engagement and communication skills—capable of translating complex analytics concepts into actionable business strategies.
• Strong project management and interpersonal skills, with the ability to lead diverse teams and manage multiple competing priorities.
• Strong analytical and creative problem-solving skills, with the ability to synthesize insights from disparate data sources.
• Strategic mindset with a passion for hands‑on, AI‑led innovation and continuous improvement.

Technical Skills

• Expertise of programming and data science tools (Python, R), machine learning frameworks (scikit-learn, PyTorch), large-scale analytics environments, visualization platforms, and workflow automation.
• Proficiency with causal inference and incrementality tools (geo‑experiments, matched markets, synthetic controls, uplift modeling); expertise in Bayesian/hierarchical MMx, adstock/distributed lag, and saturation/response‑curve modeling, and operationalizing these in automated pipelines and platforms.
• Deep proficiency in enabling agent collaboration, negotiation, and task orchestration, including coordination of agent roles/functions within a commercial analytics or decision‑science context.
• Experience operationalizing LLMs for commercial use cases—knowledge retrieval, summarization, generative analytics, and automation of insight generation.
• Experience with cloud analytics platforms (Databricks, Snowflake, Spark), MLOps, and BI tools.
• Strong foundation in AI governance (risk management, security, privacy, model monitoring, human‑in‑the‑loop) in regulated environments; understanding of HIPAA, GDPR/CCPA and regulatory standards.
• Familiarity with CRM (e.g., Veeva), omnichannel metrics, multi‑touch attribution (MTA), and AI‑driven next‑best‑action frameworks.

We hire for skills and capabilities, not just credentials – if this role excites you, but doesn’t perfectly match your resume, we encourage you to apply anyway.

How We Work

Where you work matters – because collaboration, innovation and patient impact happen in many settings. Our roles are structured across four work models: site-essential, site-by-design, field-based and remote-by-design. The model assigned to this role is based on its core responsibilities. Learn more at https://careers.bms.com/ways-of-working.

Supporting People with Disabilities

BMS is dedicated to ensuring that people with disabilities can excel through a transparent recruitment process, reasonable workplace accommodations/adjustments and ongoing support in their roles. Applicants can request a reasonable workplace accommodation/adjustment prior to accepting a job offer. If you require reasonable accommodations/adjustments in completing this application, or in any part of the recruitment process, direct your inquiries to [e-mail]. Visit careers.bms.com/eeo-accessibility to access our complete Equal Employment Opportunity statement.

Candidate Rights

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We’re creating innovative medicines for patients fighting serious diseases. We’re also nurturing our own diverse team with inspiring work and challenging career options. No matter the role, each one of us makes a contribution. And that makes all the difference.