Principal Analyst Decision Science and AI Enablement

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

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: