Principal Analyst Decision Science and AI Enablement

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Job Description:

OBJECTIVES / PURPOSE

We are seeking a high-caliber Principal Analyst to join Takeda's GCC Commercial Analytics & Insights (CA&I) organization in India as part of the Decision Science & AI Enablement COE. This senior individual contributor role serves as a technical and consultative anchor for complex AI/ML, advanced analytics, decision science, and GenAI workstreams supporting US and global commercial priorities.

Accountabilities

AI/ML Strategy and Delivery:

• Lead complex model development, validation, monitoring, and lifecycle management workstreams across classification, regression, NLP, recommendation, deep learning, and personalization use cases.
• Frame ambiguous commercial business problems into structured analytical approaches, identifying data requirements, methodological options, success metrics, and implementation considerations.
• Guide integration of claims, CRM, digital engagement, EMR, specialty pharmacy, omnichannel, and other commercial behavioral datasets into scalable AI/ML solutions.
• Produce executive-ready technical narratives that explain methodology, performance, limitations, business implications, and recommendations for model adoption or refinement.
  
  

Personalization and Decision Frameworks:

• Architect reusable decisioning frameworks for next-best-action / next-best-channel, patient identification, HCP targeting, segmentation, and engagement prioritization.
• Design experimentation and measurement approaches, including A/B testing, control groups, uplift analyses, and KPI frameworks to quantify business impact.
• Partner with DD&T, Omnichannel, Marketing Operations, and analytics teams to operationalize model outputs into business workflows while preserving quality and traceability.
  
  

Innovation and GenAI:

• Lead evaluation and prototyping of GenAI and LLM-based solutions for insight synthesis, content support, literature and knowledge retrieval, and intelligent assistants for analytics teams.
• Define evaluation criteria, quality gates, and documentation standards for GenAI pilots so outputs are transparent, reliable, and aligned with approved guardrails.
• Convert successful prototypes into reusable analytical assets, prompts, code patterns, and implementation playbooks that can be leveraged across brands and markets.
  
  

COE Excellence and Methodology Standards:

• Provide technical guidance, code review, model review, and methodology coaching to Senior Analysts and Analysts across assigned workstreams.
• Establish and maintain best-practice libraries, reusable modeling templates, validation checklists, and documentation standards for the Decision Science & AI Enablement COE.
• Contribute to COE capability building by sharing emerging methods, automation opportunities, and practical applications of AI/ML and GenAI in commercial pharma analytics.
  
  

Knowledge, Skills & Experience

Education:

• Bachelor's or master's degree required in Computer Science, Data Science, Statistics, Engineering, Mathematics, Operations Research, or a related quantitative field.
• Advanced degree in Data Science, Statistics, Computer Science, Engineering, or a related quantitative field is strongly preferred.
  
  

Experience:

• 5–6 years of progressive experience in AI/ML, data science, advanced analytics or predictive analytics in the pharmaceutical space
• Demonstrated experience independently leading complex model development, decision science, experimentation, or personalization workstreams.
• Advanced proficiency in Python, SQL, and applied machine learning methods; working knowledge of Spark/PySpark, Databricks, and cloud-based ML platforms is preferred.
• Applied experience with commercial pharma or healthcare datasets such as claims, CRM, digital engagement, EMR, specialty pharmacy, omnichannel interaction, or sales data.
• Experience with model deployment, monitoring, documentation, and lifecycle management practices is strongly preferred.
• Experience partnering with commercial, omnichannel, DD&T, or AI/ML engineering stakeholders in a matrixed environment is preferred.
  
  

Skills & Competencies:

• Advanced AI/ML Expertise — Designs and guides complex analytical methodologies across predictive modeling, NLP, recommendation systems, personalization, and experimentation.
• Consultative Partnership — Frames business questions, recommends analytical approaches, and influences stakeholders through clear technical and commercial reasoning.
• Technical Proficiency — Advanced Python and SQL; strong understanding of ML frameworks, Databricks, Spark/PySpark, cloud ML platforms, and model monitoring practices.
• Decision Science Leadership — Builds reusable decisioning frameworks that connect model outputs to commercial workflows and measurable business outcomes.
• GenAI Enablement — Evaluates LLM-based solutions, defines quality standards, and translates prototypes into reusable assets under approved guardrails.
• Data Storytelling — Synthesizes complex model results into concise, decision-oriented narratives for senior technical and business audiences.
• Informal Leadership — Provides technical mentorship, methodology review, and best-practice guidance across the COE.
  
  

TAKEDA BEHAVIORS

In alignment with Takeda's Values-Based Culture, this role requires demonstration of the following leadership behaviors

• Act with Integrity — Deliver accurate, transparent work and take full responsibility for quality.
• ;>Act with Integrity — Deliver accurate, transparent work and take full responsibility for quality.;>Act with Integrity — Deliver accurate, transparent work and take full responsibility for quality.
• Collaborate Cross-Functionally — Contribute positively to GCC-US team workflows and cross-functional collaboration.
• ;>Collaborate Cross-Functionally — Contribute positively to GCC-US team workflows and cross-functional collaboration.;>Collaborate Cross-Functionally — Contribute positively to GCC-US team workflows and cross-functional collaboration.
• Drive Accountability — Take ownership of all assigned tasks and deliver on commitments.
• ;>Drive Accountability — Take ownership of all assigned tasks and deliver on commitments.;>Drive Accountability — Take ownership of all assigned tasks and deliver on commitments.
• Embrace Learning — Continuously build analytical and domain capabilities through feedback and self-driven development.
• ;>Embrace Learning — Continuously build analytical and domain capabilities through feedback and self-driven development.;>Embrace Learning — Continuously build analytical and domain capabilities through feedback and self-driven development.
  
  

Locations:

IND - Bengaluru

Worker Type:

Employee

Worker Sub-Type:

Regular

Time Type:

Full time