MSAT AI Lead

By clicking the “Apply” button, I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takeda’s Privacy Notice and Terms of Use .  I further attest that all information I submit in my employment application is true to the best of my knowledge. Job Description ROLE: MSAT AI LEAD LOCATION : BENGALURU OBJECTIVE: - Operationalize the MSAT AI strategy, translating scientific and operational requirements into scaled solutions within Takeda’s EDB (enterprise data backbone) - Develop agentic AI solutions within Databricks and any other GSQ approved NorthStar platform - Manage, govern MSAT agentic AI solutions in alignment with SAFe principles & agile delivery practices - Create measurable business value through process optimization, MSAT workflow automation, agentic troubleshooting, knowledge management, and accelerated decision-making in GSQ MSAT - Monitor digital adoption and foster community of practices for agentic AI in MSAT ACCOUNTABILITIES: - Define and execute the MSAT AI roadmap aligned with business priorities of all modalities. - Develop & deploy AI-enabled data and process knowledge [DK1] products including, but not exhaustive, predictive process monitoring, CPV intelligence, yield optimization, process capability analytics, and digital copilots. - Partner with MSAT, Manufacturing, Quality, ICC, and DD&T teams to identify high-value AI use cases. - Establish AI product lifecycle management from ideation and experimentation through deployment, validation, monitoring, and continuous improvement. - Lead AI governance including model risk management, explainability, compliance, and responsible AI practices. - Support the standardization of data models, ontologies, taxonomies required for AI scalability. - Champion digital adoption through training, coaching, and creation of AI communities of practice. - Scout and evaluate emerging AI technologies, agent platforms and orchestration [DK2], model capabilities, digital twin integrations, and automation patterns; build business cases and pilots that demonstrate tangible MSAT value and scalability DIMENSIONS AND ASPECTS: Technical/Functional (Line) Expertise: - Strong understanding of the end-to-end product and process lifecycle, spanning development, technology transfer, commercial manufacturing, CPV, troubleshooting, and lifecycle management. - Deep expertise in MSAT, process engineering, manufacturing sciences, process knowledge management, and how data and knowledge are generated, contextualized, transferred, and reused across modalities and sites. - Strong understanding of AI in Databricks, generative AI, agentic workflows, prompt engineering, model evaluation, AI orchestration, retrieval-augmented generation, data integration, and workflow automation in regulated environments. - Solid knowledge of MSAT and manufacturing digital architecture, including NorthStar, PLM, ELN, MES, Discoverant, data platforms such as Databricks, digital twin environments, and enterprise integration patterns. - Strong familiarity with GxP expectations, data integrity, validation/qualification approaches, regulatory inspection readiness, cybersecurity, privacy, and responsible AI principles. Leadership: - Serve as the MSAT AI thought leader and trusted advisor. - Influence senior stakeholders and align cross-functional teams around AI-driven transformation. - Mentor scientists, engineers, and product owners in AI best practices and data-driven decision making. - Promote a culture where knowledge and insights are accessible through AI-enabled tools. Decision-making and Autonomy: - Makes informed trade-off decisions balancing business value, scientific rigor, compliance, user experience, enterprise alignment, technical feasibility, supportability, and lifecycle impact. - Operates with a high degree of autonomy within established governance, escalating decisions with clear options, rationale, risks, and quantified business impact when needed. - Resolves cross-functional barriers related to data access, architecture, regulatory expectations, AI risk, adoption, and operating model maturity. Interaction: - Partner with MSAT Process Knowledge & Network Lead in deployment of AI solutions [DK1] - Build and strengthen data & process knowledge relationships across MSAT modalities and partner functions (R&D Pharmaceutical Sciences) to align on global standards and shared data products - Interface with DD&T ICC, CMC and Process Science across modalities to define business requirements, data requirements, governance requirements Innovation: - Anticipate and respond to shifts in technology and industry trends to position Takeda at the forefront of digital and model-based manufacturing. Complexity: - Collaborate across multiple NorthStar tools and platforms to enable integrated data solutions - Balance global standards with local business and operational needs - Adapt effectively to evolving CMC data landscapes and changing business requirements EDUCATION, BEHAVIOURAL COMPETENCIES AND SKILLS: - Advanced degree (Master’s or higher) in STEM, Computer Science, Data Science, or a related field - Minimum of 8 - 10 years [DK1] of experience in the pharmaceutical or biotech industry , with expertise in CMC and/or MSAT - Strong hands-on experience with Databricks or similar - Proven track record of delivering AI data products using the SAFe (Scaled Agile Framework) methodology - Extensive experience managing and maintaining data products within GxP regulated environments - Demonstrated ability to deliver impactful solutions and drive collaboration within complex matrix organizations Locations IND - Bengaluru Worker Type Employee Worker Sub-Type Regular Time Type Full time