Senior Analyst Decision Science and AI Enablement Bengaluru, Karnataka Category: Insights & Analytics

Job description

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To be notified when applications are available again, please share your contact information here. --> Skip to main content Job Posting Find jobs for Location Radius Senior Analyst Decision Science and AI Enablement Bengaluru, Karnataka Apply Now Job ID R0191149 Category Insights & Analytics Subcategory Technology & Data Analytics Business Unit USBU (United States) Job Type Full time 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 The Future Begins Here At Takeda, we are leading digital evolution and global transformation. By building innovative solutions and future-ready capabilities, we are meeting the need of patients, our people, and the planet. Bengaluru, the city, which is India’s epicentre of Innovation, has been selected to be home to Takeda’s recently launched Innovation Capability Center. We invite you to join our digital transformation journey. In this role, you will have the opportunity to boost your skills and become the heart of an innovative engine that is contributing to global impact and improvement. At Takeda’s ICC we Unite in Diversity Takeda is committed to creating an inclusive and collaborative workplace, where individuals are recognized for their backgrounds and abilities they bring to our company. We are continuously improving our collaborators journey in Takeda, and we welcome applications from all qualified candidates. Here, you will feel welcomed, respected, and valued as an important contributor to our diverse team. OBJECTIVES / PURPOSE We are seeking a high-caliber Senior Analyst to join Takeda's GCC Commercial Analytics & Insights (CA&I) organization in India as part of the Decision Science & AI Enablement COE. This 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. · Support framing of ambiguous commercial business problems into structured analytical approaches, identifying data requirements, methodological options, success metrics, and implementation considerations. · Help in integration of claims, CRM, digital engagement, EMR, specialty pharmacy, omnichannel, and other commercial behavioral datasets into scalable AI/ML solutions. · Assist in producing executive-ready technical narratives that explain methodology, performance, limitations, business implications, and recommendations for model adoption or refinement. Personalization and Decision Frameworks · Supports implementation of reusable decisioning frameworks for next-best-action / next-best-channel, patient identification, HCP targeting, segmentation, and engagement prioritization. · Executes 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 · Support evaluation and prototyping of GenAI and LLM-based solutions for insight synthesis, content support, literature and knowledge retrieval, and intelligent assistants for analytics teams. · Implement evaluation criteria, quality gates, and documentation standards for GenAI pilots so outputs are transparent, reliable, and aligned with approved guardrails. · Support conversion of 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 · Supports code review, model review, and methodology coaching to Analysts across assigned workstreams. · Builds and maintains 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: · 4–5 years of progressive experience in AI/ML, data science, advanced analytics or predictive analytics in the pharmaceutical space · Demonstrated experience independently delivering 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 — Implements 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 Execution — Builds reusable decisioning frameworks that connect model outputs to commercial workflows and measurable business outcomes. · GenAI Enablement — Creates LLM-based solutions, establishes quality standards, and supports translation of prototypes into reusable assets under approved guardrails. · Data Storytelling — Supports synthesis of complex model results into concise, decision-oriented narratives for senior technical and business audiences. 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 positiv