OBJECTIVES / PURPOSE

We are seeking a technically strong and business-oriented data analytics manager to join Takeda's GCC Commercial Analytics & Insights organization in India as Manager, Access Data Products & AI Analytics. This role will support the delivery and operational excellence of Takeda's Patient and Market Access data product portfolio. The Manager will partner closely with the Senior Manager, Access Data Product Strategy & AI Enablement, the U.S. Access Data Products Director, Patient Access and Market Access (PAMA), DD&T; ICC teams to translate PAMA business needs into trusted, governed, analytics-ready data products and solutions. The ideal candidate will bring strong hands-on data analytics skills, commercial pharma data experience, and practical exposure to contemporary data platforms and AI-enabled analytics. Experience with Databricks, SQL, BI tools, AI/BI capabilities, conversational analytics, GenAI, LLMs, small language models, and natural language data exploration is preferred. Candidates with prior experience at organizations such as ZS, Axtria, IQVIA, or similar life sciences analytics and data consulting firms would be well aligned to this role. This role requires a hands-on manager who can manage product delivery workstreams, perform data analysis, validate business rules, support reporting and AI/BI enablement, and ensure data products and analytics are accurate, reusable, and fit for decision-making.

ACCOUNTABILITIES

- Access data product delivery and execution: Translate business questions and stakeholder needs into clear requirements, user stories, acceptance criteria, source-to-target mappings, data definitions, and validation scenarios.
- Partner with the Senior Manager, U.S. Access Data Products Director, DD&T;, data engineering teams, analytics teams, and reporting teams to ensure assigned data products are delivered with quality and business relevance.
- Maintain product backlogs, delivery trackers, issue logs, release notes, documentation, and validation evidence for assigned Access data products.
- Support standardization and reuse across Access data products, helping reduce fragmented, manual, or one-off datasets.

- Technical data analysis and Databricks enablement: Perform hands-on data analysis to profile data, validate logic, investigate discrepancies, and confirm data readiness for analytics and reporting use cases.
- Use SQL and modern data platforms, especially Databricks or similar environments, to support data exploration, transformation validation, reconciliation, and analytics-ready dataset preparation.
- Partner with data engineers and platform teams to review data models, transformation logic, refresh processes, and consumption layers.
- Support creation and validation of semantic layers, curated data marts, reusable business logic, and certified metrics for Access analytics and reporting.
- Identify opportunities to automate recurring data checks, validation routines, reporting support, and data quality monitoring.

- AI/BI and conversational analytics support: Support AI/BI and GenAI-enabled analytics use cases that improve data discovery, self-service reporting, data quality investigation, documentation, and insight generation.
- Assist in developing and validating conversational analytics capabilities,



including natural language querying, governed semantic layers, reusable analytical prompts, and business-friendly data exploration experiences.
- Bring practical understanding of LLMs, small language models, prompt engineering, retrieval-augmented generation, and responsible AI concepts as they apply to commercial pharma data and analytics.
- Partner with the Senior Manager and platform teams to test AI-enabled workflows and ensure outputs are accurate, explainable, governed, and appropriate for business use.
- Help business users adopt AI-enabled analytics capabilities by supporting training materials, FAQs, examples, documentation, and issue resolution.

- Data quality, validation, and governance: Perform hands-on data quality checks, including completeness, timeliness, accuracy, consistency, business rule adherence, and reconciliation against source or control totals.
- Create and maintain validation scripts, QA checklists, exception reports, control files, and issue-resolution documentation.
- Investigate data discrepancies, identify root causes, coordinate remediation with technical teams, and communicate business impacts clearly.
- Support data quality KPIs and monitoring routines for assigned Access data products.
- Ensure business rules, metric definitions, lineage, source-to-target mappings, transformation logic, assumptions, limitations, and known caveats are documented and maintained.
- Follow Takeda's data governance, privacy, metadata, lineage, and appropriate-use standards for healthcare and commercial pharma data.

- Reporting and analytics enablement: Support trusted home office, market access, patient services, and franchise-level reporting by ensuring assigned Access data products are accurate, timely, and decision-ready.
- Partner with A&I; and reporting teams to validate dashboards, scorecards, metrics, extracts, and analytical outputs that rely on Access data products.
- Support analytics use cases related to payer engagement, coverage and formulary performance, affordability, reimbursement, prior authorization, hub operations, specialty pharmacy performance, patient journey, and access performance measurement.
- Help identify opportunities to improve time-to-insight through reusable data logic, better documentation, improved data models, automated checks, and simplified data consumption.
- Support adoption of centralized Access data products and help transition users away from non-standard or manual reporting processes where appropriate.

- Stakeholder, vendor, and team collaboration: Work closely with U.S. and GCC stakeholders across PAMA, A&I;, Commercial Operations, DD&T;, franchise analytics teams, and vendors to clarify requirements, resolve issues, and support delivery.
- Collaborate with external data and analytics partners as needed, including vendors and consulting partners supporting Access data, commercial pharma analytics, data engineering,



and AI-enabled analytics.
- Bring working knowledge of commercial pharma data vendor ecosystems, including IQVIA, Axtria, ZS, specialty pharmacy data partners, hub vendors, claims vendors, payer/formulary data providers, and related partners.
- Communicate status, risks, dependencies, issues, and decisions clearly to the Senior Manager and relevant stakeholders.
- Manage and coach a small team of analysts, QA resources, or reporting specialists supporting assigned Access data product workstreams.

KNOWLEDGE, SKILLS & EXPERIENCE Education

Bachelors degree in Statistics, Business, Information Systems, Computer Science, Engineering, Analytics, Life Sciences, or a related field required.

Experience

- 7+ years of experience in data analytics, business intelligence, reporting, data product delivery, data operations, commercial analytics, or business analysis.
- Experience in pharmaceutical, biotech, healthcare, payer, patient services, market access, or life sciences data preferred.
- Experience leading small teams, delivery workstreams, analysts, QA resources, or reporting specialists.
- Experience translating business needs into requirements, user stories, data definitions, source-to-target mappings, testing scenarios, and validation plans.
- Experience with commercial pharma data sources such as claims, specialty pharmacy, hub, payer, plan, formulary, IQVIA, LAAD, LAAD Plus, DDD, 852/867, patient services, market access, or affordability data preferred.
- Prior experience with ZS, Axtria, IQVIA, or similar life sciences analytics, data strategy, or consulting organizations preferred.
- Experience supporting U.S. commercial pharma stakeholders across Market Access, Patient Services, Commercial Operations, Analytics & Insights, or brand/franchise teams preferred.

Technical skills
- Strong Python and SQL skills required.
- Hands-on experience with data analysis, data profiling, reconciliation, validation, QA, and root-cause investigation required.
- Experience with Databricks or similar cloud data platforms preferred.
- Familiarity with Spark, PySpark, Python, notebooks, data pipelines, semantic layers, and modern ELT concepts preferred.
- Experience with BI and visualization tools such as Tableau, Power BI, Qlik, or similar platforms.
- Exposure to Databricks AI/BI capabilities, Genie or Gene-style conversational analytics, natural language querying, or AI-assisted data exploration preferred.
- Basic understanding of LLMs, small language models, prompt engineering, retrieval-augmented generation, conversational analytics, and responsible AI concepts preferred.
- Experience using AI or GenAI tools to improve analytics workflows, reporting, documentation, data quality, or user self-service preferred.
- Working knowledge of data modeling, metadata, lineage, source-to-target mapping, data governance, MDM, and controlled data consumption.
- Understanding of data privacy, compliance, and appropriate use considerations for healthcare and commercial pharma.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Manager, Access Data Products & AI Analytics (Bengaluru)
🏢 Takeda Pharma Vertrieb
📍 Bengaluru