Responsibilities Work with EPAM's clients and EPAM internal teams (business SME's, account management teams, etc.) to shape the AI/ML/Agentic business and technology vision and GTM offerings aligned with current and emerging needs Manage end-to-end Data Science, AI, and Agentic projects/programs Lead multidisciplinary workshops and design sessions with customers Develop high-quality proposals in conjunction with other SMEs and consultants Work on EPAM's Data Science, AI, and Agentic offerings from a point of view Take an active part in growing the EPAM team's capacity and capability including building new competencies, selecting, and mentoring new team members. Acts as an agent of change internally and a champion of transformation with external stakeholders Requirements 10+ years of experience as Data Science Lead, Machine Learning Engineering Lead, or similar roles in the Healthcare, Pharmaceutical, MedTech/BioTech space 5+ years in a leadership role with team management responsibilities Demonstrated expertise in one or more areas of the life sciences or healthcare value chain (e.g., R&D, Clinical, Commercial, Manufacturing, Payer, or Provider), pharma manufacturing Great communication skills: ability to communicate AI and LSHC concepts compellingly to a variety of audiences with ease Hands-on experience, focused in at least one of the following domains: computer vision, NLP/language models, recommender systems, time series analytics Machine Learning Engineering/ Production delivery experience, ML/LLMOps. Experience working with one or more major cloud providers Knowledge of one or more of the following technologies: Databricks, Snowflake, Agentic Orchestration (LangChain, Omnigent, Semantic Kernel, etc.) Working knowledge of at least one programming language, ideally Python Understanding of Data Science engineering excellence and the modern SDLC for AI products Consulting experience (internal or through a professional services firm) Nice to have Currently acting as an AI leader for a healthcare or life science organization Referenceable work (papers, open-source contributions, conference talks) around the AI / ML space Current cloud certifications for at least one of: AWS, GCP, Azure, Databricks Experience navigating regulatory processes, ISO/IEC Standards, HIPAA, EU AI Act, GxP, etc.