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- Type
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Principal Analyst Decision Science and AI Enablement
- Location
- Bengaluru
- Type
- Full time
- Posted
- 11D AGO
About the role
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:
- 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 - BengaluruWorker Type
EmployeeWorker Sub-Type
RegularTime Type
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