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EPAM ищет руководителя направления Data & AI Delivery для работы в Польше. В обязанности входит ведение крупных проектов, координация команд и взаимодействие с заказчиками на уровне топ-менеджмента, формирование стратегий данных и трансформационных программ.
Необходимо глубокое понимание домена Pharma/LCMS и способность описывать бизнес-ценность решений. Кандидат должен уметь прототипировать аналитические решения, проводить работы с рабочими сессиями и руководить изменениями.
EPAM's Data & AI Practice helps pharmaceutical and life sciences companies develop analytics and AI strategies, data platforms, and AI-driven transformation programs that deliver measurable commercial value.
Manage and coordinate consulting engagements end-to-end, owning delivery output, quality, and client satisfaction; Drive major pillars of broader data strategy and transformation programs; Discover data, analytics, and AI opportunities with customer business stakeholders; Design and drive executive workshops and stakeholder interviews; Define and prioritize strategic and immediate business needs; Map customer vision and requirements to data products, AI products, platforms, and solutions; Drive collaborative ideation sessions with client stakeholders and internal cross-functional teams; Envision, prototype, and oversee analytical solutions based on commercial domain expertise and business goals; Drive guided analytics using non-standard visualization techniques and ad-hoc analytics in executive discussions; Define success measures with clients and track realized value after go-live; Track adoption levels and change management required to achieve adoption; Collaborate with data engineering and architecture teams; Participate in decisions regarding team structures, composition, and talent selection; Partner with account managers to build, grow, and retain strategic customer relationships; Participate in pre-sales and up-sales initiatives; Navigate high ambiguity before discovery phases to understand client business needs; Respond to RFxs, create proposals, and present them to potential clients; Develop sales and field force analytics, including territory alignment, HCP targeting, incentive compensation, and engagement effectiveness; Develop marketing and brand analytics, including market share, competitive benchmarking, market landscape, and launch performance analytics; Develop customer engagement and omnichannel solutions, including HCP/HCO 360 data products and next-best-action models; Develop market access, patient, and payer analytics; Build commercial data foundations, including syndicated data integration, CRM platforms, claims and real-world data harmonization, and master data management; Develop AI and conversational analytics, including natural-language query assistants, commercial copilots, insight synthesis agents, and agentic workflows.
10+ Years of total experience in data, analytics, and/or AI; 3+ Years in product, delivery, consulting, or presales roles; 5+ Years of experience in Life Sciences / Pharma; Expert knowledge of Pharma Commercial domains, including sales, marketing, customer engagement, brand strategy, and omnichannel analytics; Experience managing enterprise data products across the full product lifecycle, including data platforms, data warehouses, data lakes, BI, and advanced analytics solutions; Experience managing AI products and understanding how they differ from analytics products; Ability to facilitate and drive executive-level strategy discussions, including value articulation and value realization tracking; Experience working with end-users, driving product design, running UATs, and facilitating and measuring adoption; Experience with end-to-end delivery of cloud data platforms, BI/reporting, data catalogs or marketplaces, analytics migration and modernization, predictive analytics and 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 and presentation skills, with comfort in technical and executive discussions; Ability to manage customer expectations and explain project deliverables to senior stakeholders; Ability to have honest conversations about AI capabilities and limitations; Ability to frame a presales opportunity into a customer engagement; Passion for the Data & AI space and a track record of staying ahead of the curve; Growth mindset and willingness to learn, experiment, and expand professional comfort zones; Nice to have: Familiarity with industry data and platforms such as IQVIA, Veeva, and SAP; German, Spanish, or French language proficiency.
No conditions specified