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

EPAM Systems is a global leader in AI transformation engineering and integrated consulting, serving Forbes Global 2000 companies and ambitious startups with over thirty years of expertise in custom software, product and platform engineering.

• 10+ years of experience in data, analytics, or AI domains
• 3+ years in product, delivery, consulting, or presales roles
• 5+ years experience in Life Sciences / Pharma with expert knowledge of Pharma Commercial domains
• Proficiency in German, Spanish, or French is a strong plus
• Experience managing data products across full lifecycle, including platforms, warehouses, lakes, BI, and advanced analytics
• Experience managing AI products and understanding their distinctions from analytics products
• Ability to drive strategy discussions at executive levels and track value realization
• Experience with end-user engagement for product design, UATs, and adoption measurement
• Experience with 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 and programs
• Proven leadership of project teams of 10+ individuals
• Excellent communication and presentation skills for technical and executive audiences
• Ability to manage customer expectations and explain AI capabilities and limitations
• Strong presales opportunity framing skills
• Passion for Data & AI with a growth mindset

• 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 and prioritize needs
• Map customer requirements to specific data and AI products and solutions using appropriate product management techniques
• Envision, prototype, and oversee implementation of analytical solutions in sales, marketing, and market access domains
• Drive value realization, governance, operational change management, and define success measures with clients
• Collaborate with data engineering and architecture teams on modern cloud data platforms and data architectures
• Participate in team structuring and talent selection to ensure delivery excellence
• Partner with account managers to build and retain strategic customer relationships
• Participate in pre-sales and up-sales, responding to RFxs and creating proposals
• Lead analytics in sales & field force, marketing & brand, customer engagement & omnichannel, market access, and commercial data foundation
• Oversee AI and conversational analytics products including natural-language query assistants and automation workflows

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