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

EPAM is a global leader in AI transformation engineering and integrated consulting, serving Forbes Global 2000 companies and startups. They have over thirty years of expertise in custom software, product and platform engineering, empowering clients to become AI-Native enterprises.

• 10+ years of experience in data, analytics, and/or AI domains.
• 3+ years in product, delivery, consulting, or presales roles.
• 5+ years of Life Sciences / Pharma experience with expert knowledge in Pharma Commercial domains.
• Familiarity with industry data platforms such as IQVIA, Veeva, SAP is a strong plus.
• Experience managing data products across full lifecycle including platforms, warehouses, lakes, BI, and analytics.
• Experience managing AI products and understanding their distinctions from analytics products.
• Ability to facilitate executive strategy discussions and track value realization.
• Experience working with end-users, driving product design, UATs, and measuring adoption.
• Experience in end-to-end project delivery involving Cloud Data Platforms, BI/Reporting, Data Catalogs, Analytics Migration, Predictive Analytics, Generative AI, and Agentic Systems.
• Exposure to complex multi-market or cross-domain products.
• Leadership experience managing project teams of 10+ individuals.
• Excellent communication and presentation skills for both technical and executive audiences.
• Ability to manage customer expectations and transparently communicate AI capabilities and limitations.
• Ability to convert presales opportunities into customer engagements.
• Passion for Data & AI and continuous learning mindset.
• German, Spanish, or French language proficiency is a strong plus.

• Manage and coordinate consulting engagements end-to-end, ensuring delivery output, quality, and client satisfaction.
• Engage with customer business stakeholders to identify data, analytics, and AI opportunities.
• Design and drive executive workshops and stakeholder interviews to prioritize strategic needs.
• Map customer vision to specific data products, AI products, platforms, and solutions using appropriate product management techniques.
• Envision, prototype, and oversee implementation of analytical solutions based on commercial domain expertise.
• Engage with clients on value realization, governance, operational change management, and roadmap planning.
• Collaborate with data engineering and architecture teams to bridge business needs with technical delivery.
• Participate in decisions regarding team structures and project staffing.
• Partner with account managers to develop strategic customer relationships.
• Participate in pre-sales and up-sales initiatives, including proposal creation and presentations.
• Address sales & field force analytics, marketing & brand analytics, customer engagement & omnichannel analytics, market access, patient & payer analytics, and commercial data foundation.
• Lead AI & conversational analytics initiatives such as natural-language query assistants and automation of commercial reporting.

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