Technical Product Manager – Lilly USA Data Analytics & AI

Overview

Own the product vision, roadmap, prioritization and value realization for Lilly USA Commercial Sales data and analytics products, translating Sales Operations, field leadership and commercial needs into trusted, reusable data products. This is an individual-contributor role within Tech@Lilly – DA&AI, reporting to the Director, CTI Commercial India, Tech@Lilly.

What you'll do

• Define and communicate a multi-quarter data-product vision and roadmap for Commercial Sales, aligned with Commercial Unit priorities and the broader Data & AI strategy.
• Translate business problems such as field effectiveness, targeting and customer engagement into validated product opportunities, data requirements and measurable outcomes.
• Prioritize the roadmap and backlog using business value, urgency, strategic alignment, effort, risk, compliance, capacity and dependency trade-offs; make and defend scope decisions with leadership.
• Maintain a transparent roadmap, release outlook and product lifecycle plan, clearly communicating changes in priorities, capacity, funding or dependencies.
• Align the Sales roadmap with reusable enterprise capabilities, platform roadmaps and relevant AI innovation initiatives before approving vertical-specific development.
• Lead structured discovery with field users, Sales Operations and reporting teams to understand decisions, workflows, unmet needs and pain points before defining solutions.
• Validate problems and proposed product concepts through interviews, workflow observation, prototypes, data analysis, usability testing and field feedback.
• Define the business contract for each Sales data product, including intended consumers, decision use cases, product grain, key identifiers, business definitions, source systems, refresh expectations, quality thresholds, access requirements and service expectations, in partnership with the Business Analyst and Data Architect.
• Maintain a clear product catalogue covering product purpose, business owner, product owner, consumers, lifecycle status, dependencies, service expectations and adoption measures.
• Own product outcomes from validated opportunity through production adoption, including scope, prioritization, release decisions, enablement and post-launch value tracking.
• Partner with the Business Analyst to translate outcomes into epics, features, user stories, data requirements and acceptance criteria.
• Partner with the Scrum Master so planning refinement, reviews and delivery ceremonies support product priorities and timely decisions.
• Work with data engineers, analysts, ML engineers, quality teams and architects to resolve product questions and make informed value, usability, risk and sequencing trade-offs.
• Establish business acceptance criteria, coordinate UAT with authorized Sales stakeholders and secure business sign-off before release.
• Ensure critical Sales measures are reconciled across source systems, data products and consuming reports before production adoption.
• Coordinate product acceptance and operational handover to downstream analytics and reporting teams, including documentation, access, support ownership and known limitations.
• Track delivery and product health, proactively surfacing risks, dependencies, quality concerns, cost considerations and mitigation decisions.
• Act as the single point of accountability and voice of the product for Commercial business partners, Sales Operations, field leadership and technology stakeholders.
• Lead regular Sales product reviews covering roadmap, value realized, adoption, product health, dependencies, risks and decisions required.
• Lead quarterly demand, capacity and sequencing discussions for the Sales data-product portfolio, balancing business value, urgency, strategic alignment, risk, technical dependencies and available delivery capacity.
• Assess existing enterprise data products, approved patterns and reusable platform capabilities before starting new development.
• Contribute to maintaining the Sales DA&AI operating model, decision rights and RACI, recommending updates when product, platform or delivery accountabilities change.
• Provide concise executive updates and evidence-based investment recommendations, including the consequences of funding, capacity and sequencing decisions.
• Champion and apply architecture, data-governance, privacy, security, quality and compliance standards established by the accountable enterprise teams.
• Promote trusted business definitions, data quality, lineage, appropriate access and a consistent source of truth for Sales and Commercial measures.
• Identify and validate Sales problems that may benefit from analytics, machine learning, generative AI or agentic capabilities.
• Partner with Business Analysts and engineering teams to assess feasibility, data readiness, responsible-AI considerations and measurable business value.
• Support the transition of successful proofs of concept into governed, supportable and adoptable Sales products.
• Define success measures before investment and track outcomes after release, using appropriate business, product, data-quality, adoption and delivery measures.
• Drive change management, training, communications and field enablement so intended users adopt and benefit from the products.
• Continuously improve products through evidence-based releases, address low adoption or quality concerns and retire low-value or duplicative capabilities.

What you'll need

• Relevant experience in technology, data, analytics or digital product delivery, including substantial experience owning data, analytics or AI products in complex enterprise environments.
• Proven record of owning product discovery, vision, roadmap, prioritization, delivery, adoption and lifecycle management in an Agile environment such as Scrum or SAFe.
• Experience working with Commercial Sales, Sales Operations, CRM, field-force or customer-engagement data and platforms such as Salesforce, Veeva or similar.
• Strong data literacy, including the ability to interpret data models, SQL outputs, dashboards, business measures, quality indicators and analytical results.
• Working knowledge of modern cloud data and analytics platforms, such as Databricks and AWS, including Lakehouse concepts, data pipelines, data modelling, semantic layers, business intelligence and ML/AI product lifecycles.
• Not expected to be a hands-on data engineer, but must engage credibly with technical teams and make informed product trade-offs.
• Experience with product discovery, outcome-based roadmaps, business acceptance, UAT, product adoption and measurable product KPIs.
• Experience managing priorities, dependencies, capacity and sequencing across multiple business and delivery teams.
• Working knowledge of Jira or Azure DevOps for product backlog and roadmap management.
• Demonstrated understanding of data governance, privacy, security, quality, compliance and responsible AI in a regulated environment.
• Excellent written and verbal communication, stakeholder management, negotiation and consulting skills, including the ability to influence senior leaders and global cross-time-zone teams without formal authority.

Nice to have

• Pharma, life sciences or healthcare Commercial experience across brand, sales operations, market access, marketing analytics or omnichannel engagement.
• Experience with AI/ML or generative-AI product use cases such as next-best action, forecasting, recommendation or copilots for Sales users.
• Experience handing data products over to downstream analytics, reporting or decision-support platforms.
• Familiarity with tools and services such as Confluence, Databricks, AWS, Power BI, Tableau, Redshift or Amazon S3.
• One of the Product or Agile certifications such as CSPO, SAFe POPM or PMP.

Details

• Location: India – Bangalore.
• Reports to Director, CTI Commercial India, Tech@Lilly.
• Path/Level P3; roles are posted at the lowest level of a band.
• Must have or obtain work authorization in the country where the position is to be considered.