Head of Decision Science and AI Enablement COE (Director)

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Job Description

OBJECTIVES / PURPOSE

We are seeking an innovative and experienced AI/ML leader to join Takedas newly established GCC Commercial Analytics & Insights (CA&I) organization in India as the Decision Science and AI Enablement COE Lead. This Center of Excellence (COE) role is foundational in building and scaling Takedas centralized decision science and AI capabilities to drive data-driven commercial outcomes across all Business Units.

• Lead the Decision Science & AI Enablement Center of Excellence within Takedas GCC Commercial Insights & Analytics organization in India providing centralized AI/ML capabilities for US and global commercial teams.
• Partner with US and International I&A brand omnichannel operations and access teams to identify highvalue use cases and embed modeldriven decisioning into business workflows (e.g. patient identification HCP targeting nextbestaction).
• Set and execute the AI/ML strategy and roadmap for commercial analytics ensuring solutions are robust explainable compliant and aligned with priority brands and portfolios.
• Build and develop Indiabased pods of data scientists and ML engineers that operate as an embedded extension of US/Global I&A fostering a culture of scientific rigor innovation and continuous learning.

ACCOUNTABILITIES

AI/ML strategy and delivery

• Define and maintain the commercial AI/ML roadmap in partnership with US global I&A and business stakeholders spanning ideation prioritization and delivery of highimpact use cases.
• Lead development validation and deployment of models (e.g. classification regression NLP recommendation deep learning) using commercial datasets such as claims EMR specialty pharmacy CRM and digital engagement.
• Ensure models are documented monitored and governed appropriately with clear performance metrics explainability and lifecycle management.

Personalization and decision frameworks

• Design and evolve decisioning frameworks (e.g. nextbestaction / nextbestchannel targeting and segmentation engines) that can be reused across brands and markets.
• Partner with DD&T omnichannel field and marketing operations to integrate models into production systems and campaign workflows with appropriate testing and control groups.
• Define and track KPIs to measure the business impact of AIenabled decisions using experimentation and A/B testing where appropriate.

Innovation and GenAI

• Lead exploration and adoption of Generative AI and LLMbased solutions for commercial use cases such as content generation literature and insight synthesis and intelligent assistants for analytics teams.
• Ensure that the team adheres to the standards and guardrails for responsible AI use including risk assessment compliance and privacy considerations
• Maintain external relationships (vendors platforms academic partners) to keep the COE at the forefront of AI innovation.

Talent development and COE excellence

• Build lead and develop Indiabased pods of data scientists ML engineers and decision science analysts that support specific BUs/franchises.
• Set clear objectives development plans and ways of working that deepen both technical and business expertise in commercial decision science.
• Productize analytics and insights solutions appropriately to deploy frequently used applications at scale champion knowledge sharing code reuse and bestpractice libraries so models and methods can be leveraged efficiently across brands and markets.

KNOWLEDGE SKILLS & EXPERIENCE

Education

• Masters or Ph.D. in Computer Science Data Science Statistics Engineering Mathematics or a related quantitative field.

Experience

• 10 years in AI/ML data science or advanced analytics; 5 years in the US Pharmaceutical industry.
• 5 years leading data science/ML teams in a matrixed global or GCC/offshore environment.
• Experience working with commercial pharma data (e.g. IQVIA Veeva specialty pharmacy claims digital) and strong understanding of privacy/compliance requirements.

Technical skills

• Deep expertise in machine learning NLP recommendation systems and personalization of use cases.
• Proficiency in Python (preferred) plus R/SQL/Spark and experience with cloudbased ML platforms (e.g. AWS Azure GCP).
• Handson experience with MLOps practices model deployment monitoring and productiongrade ML systems.
• Experience with Generative AI and LLM frameworks and their application to commercial pharma problems.
• Knowledge of experiment design A/B testing and causal inference techniques.

Leadership & business competencies

• Proven ability to translate business needs into a clear AI/ML roadmap and communicate complex concepts in simple businessrelevant terms.
• Strong stakeholder management and collaboration skills with experience working across functions and geographies.
• Track record of delivering innovative AI solutions while maintaining high standards for ethics compliance and quality.

TAKEDA LEADERSHIP BEHAVIORS

• Think Strategically Demonstrate strategic enterprise thinking to find innovative ways to serve patients.
• Collaborate Cross-Functionally Build diverse teams that deliver results while fostering inclusion.
• Drive Accountability Execute with excellence and hold oneself and others accountable.
• Develop Talent Attract develop and retain top talent building capabilities for the future.

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