MSAT AI Lead

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ROLE: MSAT AI LEAD

LOCATION : BENGALURU

OBJECTIVE:

• Operationalize the MSAT AI strategy translating scientific and operational requirements into scaled solutions within Takedas 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 knowledgeDK1products 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 (Masters or higher) in STEM Computer Science Data Science or a related field
• Minimum of 8 - 10 years DK1of 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