Principal Analyst Decision Science and AI Enablement

Overview

Senior individual contributor role within Takeda's GCC Commercial Analytics & Insights organization in India, serving as a technical and consultative anchor for complex AI/ML, advanced analytics, decision science, and GenAI workstreams supporting US and global commercial priorities.

What you'll do

• 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.
• 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.
• 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.
• 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.

What you'll need

• Bachelor's or master's degree in Computer Science, Data Science, Statistics, Engineering, Mathematics, Operations Research, or a related quantitative field.
• 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.
• Applied experience with commercial pharma or healthcare datasets such as claims, CRM, digital engagement, EMR, specialty pharmacy, omnichannel interaction, or sales data.

Nice to have

• Advanced degree in Data Science, Statistics, Computer Science, Engineering, or a related quantitative field.
• Working knowledge of Spark/PySpark, Databricks, and cloud-based ML platforms.
• Experience with model deployment, monitoring, documentation, and lifecycle management practices.
• Experience partnering with commercial, omnichannel, DD&T, or AI/ML engineering stakeholders in a matrixed environment.

Details

• Location: IND - Bengaluru.
• Worker type: Employee; sub-type Regular.
• Time type: Full time.