Data & AI Product Manager/Senior Product Manager in Pharma Commercial

EPAM Systems; Poland; On-site; PLN 240,000 - 430,000; Full time

Job summary

EPAM Systems is seeking a Manager / Senior Manager, AI & Data Consulting specialized in Pharma Commercial to lead AI-driven transformation for global pharma clients. You will own program-level outcomes, shape data and product strategy at senior stakeholder level, and help with pre-sales and up-sales in ambiguity.

You will build and lead high-caliber teams, collaborate with account teams, and advance analytics across sales, marketing, market access, and payer analytics, leveraging GenAI, ML, and

Qualifications

• 10+ years of total experience in data, analytics, and AI.
• 3+ years in product, delivery, consulting, or presales.
• 5+ years in Life Sciences / Pharma with domain knowledge.
• Familiarity with IQVIA, Veeva, SAP; multilingual bonus.
• Experience managing data products across platforms and BI.
• Experience managing AI products and differentiating from analytics.
• Ability to drive strategy discussions at executive level.
• Experience in end-to-end delivery across cloud data platforms.
• Track record of leading project teams of 10+.
• Excellent communication and executive presentation skills.
• Presales framing and customer engagement ability.

Job description

Are you energized by turning ambiguous business challenges in the pharmaceutical and life sciences sector into intelligent, data-driven strategies and products that reshape how commercial enterprises operate? Do you see the difference between shipping a standard dashboard and shaping an enterprise-wide commercial data & AI transformation — and get excited about the latter? If you're strategic, resilient, naturally engaging, and thrive at the intersection of pharma commercial value, data architecture, and emerging AI, this could be your next chapter at EPAM. EPAM's Data & AI Practice is hiring a Manager / Senior Manager, AI & Data Consulting specialized in Pharma Commercial to help our clients craft analytics and AI strategies, design best-in-class data & AI platforms, and lead the AI-driven transformation of their enterprises. You'll work shoulder-to-shoulder with industry leaders translating cutting-edge capabilities (GenAI, agentic systems, ML, advanced analytics) into programs that move the needle. We're passionate about delivering measurable value from data and AI, and we're looking for people who share that mindset. You won't just advise or manage individual products — you'll own program-level outcomes, shape commercial product and data strategy at the senior stakeholder level, participate in pre-sales and up-sales under conditions of high ambiguity, build and lead high-caliber teams, and have direct influence on how top global pharma companies adopt AI and data responsibly and effectively.

Responsibilities

• Manage and coordinate consulting engagements end-to-end, owning delivery output, quality, and client satisfaction, or driving major pillars of broader data strategy and transformation programs
• Engage with customer business stakeholders to discover data, analytics, and AI opportunities — spanning from platform to analytics to GenAI and agentic use cases.
• Design and drive executive workshops and stakeholder interviews to define and prioritize strategic and immediate needs
• Map customer vision and requirements to specific data products, AI products, platforms, and solutions, applying the right product management techniques to each.
• Drive collaborative ideation sessions with client stakeholders and internal cross-functional teams to conceptualize target solutions
• Envision, prototype, and oversee the implementation of analytical solutions based on deep commercial domain expertise (sales, marketing, market access, etc.) and business goals.
• Drive guided analytics to solve complex challenges, leveraging non-standard visualization techniques and ad-hoc analytics in executive discussions
• Engage with clients on broader strategic dimensions—such as value realization, governance, operational change management, and what constitutes a winning roadmap of commercial analytics and AI products.
• Define success measures with the client at the outset and track realized value after go-live, including adoption levels and change management needed to reach them
• Collaborate effectively with data engineering and architecture teams.
• You bring a strong conceptual understanding of modern cloud data platforms (such as AWS, Azure, or Databricks) and modern data architectures (Data Lakes, Data Warehouses, Data Mesh), allowing you to bridge business commercial needs with technical delivery without needing to write production code
• As a trusted vendor partner, participate in decisions regarding team structures, composition, and the selection of top-tier talent to ensure delivery excellence and right-fit project staffing
• Partner with account managers to build, grow, and retain strategic customer relationships
• Partner with business development to participate in pre-sales and up-sales initiatives.
• Navigate high ambiguity before discovery phases to understand client business needs.
• Respond to RFxs, create compelling proposals, and present them to potential clients
• Sales & field force analytics: territory alignment and sizing models, HCP targeting and segmentation, incentive compensation modeling, rep vs. digital engagement effectiveness measurement
• Marketing & brand analytics: brand and market share analytics, competitive benchmarking analytics, market landscape and signal detection, launch performance analytics, competitive intelligence data products
• Customer engagement & omnichannel: HCP/HCO 360 data products, next-best-channel/next-best-action models, content and channel effectiveness analytics, engagement propensity scoring
• Market access, patient & payer analytics: patient journey and adherence/persistency modelling, payer mix and access analytics, patient support program performance measurement
• Commercial data foundation: syndicated data integration (e.g., IQVIA, GERS, or local market equivalents), CRM platforms (e.g., Veeva or similar), claims and real-world data harmonization, HCP/HCO master data management, commercial data lake/warehouse modernization, data quality and governance for regulated commercial data
• AI & conversational analytics: "ask-your-data" and natural-language query assistants, commercial copilots for brand and marketing teams, insight and literature synthesis agents, automation of commercial reporting and analysis, agentic workflows for commercial ops

Requirements

• 10+ years of total experience in the data, analytics, and/or AI domain
• 3+ years in product, delivery, consulting, or presales roles
• 5+ years in Life Sciences / Pharma. Have expert knowledge and understanding of Pharma Commercial domain areas (sales, marketing, customer engagement, brand strategy, omnichannel analytics).
• Familiarity with industry data and platforms (such as IQVIA, Veeva, SAP, data) is a strong plus German, Spanish, or French language proficiency is a strong plus
• Demonstrated experience managing data products for enterprises — including data platforms, data warehouses, data lakes, BI, and advanced analytics solutions — across the full product lifecycle
• Demonstrated experience managing AI products and a clear understanding of how they differ from analytics products
• Ability to facilitate and drive strategy discussions at executive level, including value articulation and tracking of value realization
• Experience working with end-users driving product design, running UATs, and facilitating and measuring adoption
• Experience in end-to-end project delivery as part of the team: Cloud Data Platforms, BI/Reporting, Data Catalog / Marketplace, Analytics Migration & Modernization, Predictive Analytics & ML, Generative AI, and Agentic Systems
• Exposure to complex multi-market or cross-domain products and programs
• Track record of leading project teams of 10+ individuals
• Excellent communication skills and dynamic presenter — equally comfortable with technical depth and executive narratives
• Ability to manage customer expectations, present and explain project deliverables to senior stakeholders, and have honest conversations about what AI can and can't do
• Ability to frame a presales opportunity into a customer engagement
• A genuine passion for the Data & AI space and a track record of staying ahead of the curve
• A growth mindset — eager to learn, experiment, and expand your comfort zone as the Data and AI landscape evolves