Commercial Data Ecosystems and AI readiness Lead at Takeda Pharmaceuticals

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

16 Aug, 26

Salary

0.0

Posted On

18 May, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Governance, AI Readiness, Metadata Management, Semantic Interoperability, Enterprise Data Strategy, GenAI, RAG, Knowledge Graph, Stakeholder Management, Cloud Data Platforms, Ontology Alignment, Data Quality, Cross-functional Leadership, Strategic Thinking, Analytical Decision Making, Storytelling

Industry

Pharmaceutical Manufacturing

Description

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 ABOUT THE ROLE: The Commercial Data Ecosystems & AI Readiness Lead is responsible for building and governing scalable, trusted, and AI-ready commercial data foundations across CEE GTM platforms and capabilities. The role drives alignment of commercial data, metadata, governance, and semantic standards across business units, platforms, and regions to enable analytics, GenAI, and future Agentic AI use cases. Working across Commercial, Enterprise Data & AI, AI/D, and platform teams, the role ensures commercial data ecosystems are interoperable, reusable, governed, and aligned with enterprise standards. Key responsibilities include: Defining commercial data governance and AI-readiness standards Driving metadata, lineage, data quality, and semantic consistency across platforms Enabling reusable and scalable commercial data products and services Supporting AI/GenAI use cases through trusted and contextualized data foundations Aligning commercial platforms, business units, and enterprise data capabilities Partnering with business and technology stakeholders to drive adoption and transformation ACCOUNTABILITIES: Enterprise Commercial Data Ecosystems & AI Readiness Define and operationalize the enterprise strategy for commercial data ecosystems, semantic interoperability, and AI-ready architectures across GTM platforms Establish scalable governance and operating models for commercial metadata, ontology alignment, lineage, interoperability, and reusable data assets Drive alignment between commercial business priorities, enterprise data strategy, and AI transformation initiatives Enable AI-ready data ecosystems supporting analytics, GenAI, RAG, knowledge graph, and Agentic AI capabilities Partner with enterprise data and AI organizations to ensure commercial data ecosystems align with enterprise AI, security, privacy, and governance standards Commercial Metadata, Governance & Semantic Foundations Establish and govern enterprise-wide metadata standards, business glossaries, semantic definitions, lineage frameworks, and Critical Data Elements (CDEs) Define governance frameworks for: Business metadata Technical metadata Data quality Access controls Semantic consistency Lifecycle management Lead the adoption of ontology-aligned and semantically interoperable data structures across commercial domains Govern and approve changes to commercial data definitions, lineage, semantic structures, and interoperability models across business units and geographies Ensure enterprise-critical commercial data assets are traceable to business processes, decision-making, analytics, and AI consumption layers AI & GenAI Data Enablement Enable trusted and contextualized data ecosystems supporting GenAI, RAG, intelligent search, semantic reasoning, and AI agent use cases Partner with AI and architecture teams to establish AI-ready commercial data foundations and semantic enrichment capabilities Support the operationalization of reusable commercial knowledge assets, semantic layers, and contextual data services for AI-driven capabilities Ensure commercial data ecosystems are optimized for future AI and Agentic AI scalability Stakeholder Engagement Act as a strategic advisor across commercial, data, AI, and platform organizations on commercial data and AI-readiness initiatives Build and maintain governance forums and communication channels across enterprise stakeholders Provide leadership visibility on progress, risks, priorities, and transformation outcomes Influence enterprise adoption of standards and governance practices through strong business engagement, storytelling, and technical credibility Drive alignment between enterprise transformation priorities and commercial data ecosystem capabilities EDUCATION, BEHAVIOURAL COMPETENCIES AND SKILLS: (List the essential and desirable education and competency requirements to perform the primary responsibilities of the job. Any minimum requirements should be noted.) Education Bachelor’s degree in Business, Engineering, Data/Digital, or related field (advanced degree preferred) Experience (12–14+ years) Experience in pharmaceutical, life sciences, healthcare, or other regulated industries required Strong understanding of commercial data domains and processes within pharma/life sciences environments preferred Experience supporting Commercial functions such as Customer Experience, Patient Services, Medical, Digital Health, Market Access, or Content platforms preferred Proven experience in enterprise data strategy, governance, metadata management, interoperability, and AI-ready data ecosystems Experience with cloud and enterprise data platforms (AWS, Databricks, enterprise data platforms) Familiarity with AI/GenAI data requirements including RAG, semantic search, contextualized data, and AI-driven use cases Exposure to ontology, semantic layers, knowledge graph, and enterprise metadata management concepts preferred Proven ability to work across matrixed global organizations and influence senior business and technology stakeholders Core Skills & Leadership Capabilities Strategic and enterprise-level thinking Strong analytical and data-driven decision-making capabilities Ability to translate complex technical concepts into business-relevant outcomes Strong stakeholder management and influencing capabilities Excellent communication and storytelling skills Strong cross-functional orchestration and governance leadership Self-driven with the ability to structure, prioritize, and deliver in complex enterprise environments Locations IND - Bengaluru Worker Type Employee Worker Sub-Type Regular Time Type Full time Takeda is an industry-leading, global pharmaceutical company with an unwavering dedication to putting patients at the center of everything we do. We live our values of Takeda-ism – Integrity, Fairness, Honesty, and Perseverance – and are united by our mission to strive towards Better Health and a Brighter Future for people worldwide through leading innovation in medicine. Here, everyone matters and you will be a vital contributor to our inspiring, bold mission. At Takeda, you will make an impact on people’s lives – including your own. Takeda is an equal opportunity employer. For applicants of U.S and Puerto Rico positions: Click here to learn about our commitment to Equal Employment Opportunity (EEO). If you are limited in the ability to use our job application tool, or otherwise require a reasonable accommodation for a disability please click here.

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Responsibilities

Responsible for building and governing scalable, AI-ready commercial data foundations and semantic standards across GTM platforms. The role drives alignment between commercial business priorities, enterprise data strategy, and AI transformation initiatives to enable GenAI and Agentic AI use cases.