Manager, Commercial AI Product Owner

Overview

Serve as dedicated product co-owner for the Agentic MMx and Always on Insights (AOI) Platform, a self-service analytics hub, in partnership with BI&T and Data Science, and lead the AI product lifecycle for commercial analytics capabilities.

What you'll do

• Partner on the strategy, vision, roadmap, and stakeholder alignment for the Agentic MMx and AOI Platform, and drive its evolution to advanced capabilities including MMx, scenario simulation, investment planning, constrained optimization, and real-time decision support.
• 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.
• Support monitoring and governance dashboards for model/data health, user adoption, SLAs, drift/stability, and auditability.
• Partner with BI&T, Data Science, TA Analytics, and engineering to deliver analytics-ready datasets, feature stores, semantic layers, and automated data pipelines.
• Champion automation, templated workflows, and platform creation to reduce manual effort and external vendor reliance.
• Define and track product KPIs including adoption, activation, retention, and model accuracy vs. business lift, and build training content and adoption playbooks.
• Support the design and deployment of autonomous and semi-autonomous analytics agents using multi-agent frameworks.
• Contribute to the AI product lifecycle (proof-of-concept, pilot, rollout, continuous optimization) and help 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.
• Partner with US Commercial stakeholders, Global Analytics, OCx, Marketing, UX/Design, and BI&T to understand business needs, scope analytical solutions, and design deliverables.
• Act as a strategic thought partner, helping stakeholders frame decisions, interpret insights, and understand trade-offs.
• Articulate ROI and business cases to guide AI investment, prioritization, and resource-allocation decisions.
• Collaborate with UX/Design to shape intuitive, user-centered product experiences.
• Manage and prioritize competing business demands across time zones for the Hyderabad hub.
• 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 including SLAs, RACI, privacy-by-design, and responsible/ethical AI controls.
• Ensure analytical outputs are documented, reproducible, explainable, auditable, and compliant, monitoring for bias and incorporating human-in-the-loop mechanisms where required.

What you'll need

• Advanced degree (MS/PhD) 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 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).
• Expertise in 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.
• 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.

Nice to have

• Product management/product owner certification (e.g., CSPO, SAFe PO/PM, Pragmatic Institute).

Details

• Location: Hyderabad, TS, India.
• Work model is assigned based on the role's core responsibilities, as described at careers.bms.com/ways-of-working.