Senior Product Manager - Data & AI in Clinical Trials

EPAM is 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, we empower our clients to become AI-Native enterprises, driving measurable value from innovation and digital investments.

• 10+ years experience in data, analytics, and/or AI domain.
• 5+ years experience in Life Sciences, Pharma, or CRO with clinical trial data and lifecycle knowledge.
• Experience with clinical data standards (e.g., CDISC), EDC platforms (e.g., Medidata Rave, Veeva EDC, Oracle InForm), and CTMS platforms.
• Knowledge of clinical analytics use cases including trial operations, cost analytics, site monitoring, patient recruitment, compliance reporting, pharmacovigilance.
• Familiarity with regulatory frameworks (ICH E6 GCP, 21 CFR Part 11, GDPR/HIPAA).
• Experience managing data products, including data platforms, warehouses, lakes, BI, and advanced analytics across product lifecycle.
• Experience managing AI products and understanding of differences from analytics products.
• Ability to facilitate executive strategy discussions on value articulation and realization.
• Experience driving product design, running UATs, and measuring adoption.
• Delivery experience with cloud data platforms, BI/reporting, data catalogs, analytics modernization, predictive analytics, ML, generative AI, and agentic systems.
• Leadership of project teams of 10+ professionals.
• Excellent communication and presentation skills for technical and executive audiences.
• Ability to manage customer expectations and articulate AI opportunities and limitations.
• Passion for Data & AI with a mindset for continuous learning and growth.

• Manage and coordinate consulting engagements end-to-end, ensuring delivery output, quality, and client satisfaction.
• Engage with stakeholders across Clinical Development, Clinical Data Management, Biostatistics, and R&D Data Science to identify analytics opportunities.
• Design and facilitate workshops and interviews to define and prioritize clinical analytics needs.
• Define success measures and track value realization, adoption, and change management.
• Map stakeholder vision to specific data products and analytics solutions across clinical trial domains.
• Envision, prototype, and oversee analytical solution implementation spanning site and patient lifecycle, risk-based monitoring, recruitment, operational performance, and multi-phase trial analytics.
• Drive discussions on data quality, governance, and clinical data standardization, including CDISC-aligned data models.
• Collaborate with data engineering and architecture teams, bridging clinical operational needs with technical delivery on cloud platforms like AWS, Azure, and Databricks.
• Participate in decisions on team structures and talent selection to ensure delivery excellence.
• Partner with account managers and business development teams to build customer relationships and support pre-sales initiatives.

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