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