Senior Manager, Commercial Analytics, Obesity

Career CategoryEngineeringJob DescriptionSenior Manager, Commercial Analytics Obesity Intelligence & Analytics | Amgen India Reports to: Director, Commercial Analytics Role SummaryThis is an India-based role supporting Amgen's global obesity business, with significant focus on the U.S. market. The Senior Manager serves as a strategic thought partner to global commercial stakeholders, solving high-priority business problems that influence commercial strategy, launch execution, customer engagement, and investment decisions. The role is expected to lead analytical work across the breadth of Commercial Analytics, including areas such as product strategy, launch, HCP and account engagement, field effectiveness, payer and pricing, and commercial measurement, guided by evolving business priorities. The role combines deep analytical leadership, commercial problem solving, and cross-functional influence to independently lead major commercial analytics workstreams, shaping decisions across one of Amgen's highest-priority growth businesses. Success requires strong analytical thinking, disciplined execution, stakeholder partnership, and a deep understanding of U.S. pharmaceutical commercialization. The Senior Manager owns end-to-end analytical delivery, coaches and develops team members, and helps build a flexible, high-performing Commercial Analytics capability recognized for business impact, adaptability, and execution excellence. Key Responsibilities1. Commercial Analytics Delivery & PlanningLead day-to-day analytical delivery for high-priority commercial business questions, converting stakeholder needs into practical analytical plans, timelines, deliverables, and next steps.Break business questions into clear tasks, data requirements, assumptions, review points, and decision-ready outputs.Manage scope, sequencing, dependencies, and issue escalation across parallel pieces of work while maintaining delivery quality.Partner with leadership to help shape analytical priorities, proactively identify emerging business questions, and recommend changes in focus based on evolving commercial needs.Ensure analytical outputs address the underlying business decision and provide clear recommendations for action.Serve as analytics lead and a trusted thought partner to commercial leaders, proactively identifying emerging business questions, challenging assumptions, and shaping analytical approaches that improve commercial decision making.2. Commercial Analytics Breadth & Business ContextDeliver analytical solutions across commercial priorities such as product/brand strategy, launch readiness, HCP/account engagement, field effectiveness, payer/pricing, external intelligence, and commercial measurement.Build deep commercial context across evolving business priorities, rapidly connecting market dynamics, customer behavior, competitive intelligence, and commercial execution into actionable insights.Track relevant market, customer, competitive, access/pricing, HCP behavior, and execution signals, with strong attention to U.S. dynamics.Translate internal and external information into decision-ready insights and recommendations that support stakeholder planning and execution.3. Insight Translation & Stakeholder Decision SupportSynthesize analysis across market, customer, field, access, competitive, and execution signals to clarify risks, opportunities, and practical choices.Develop national and sub-national insights that support decisions on resource allocation, launch sequencing, customer prioritization, and execution gaps.Translate sales, field activity, promotional engagement, claims, payer/pricing, access-related, market, and competitive data into decision-ready recommendations that influence commercial decisions.Frame strategic trade-offs, evaluate alternative courses of action, and recommend practical decisions supported by analytical evidence.Lead cross-functional analytical workstreams involving commercial, medical, market access, commercial operations, and product teams to develop integrated recommendations for senior stakeholders.4. Analytical Methods, Decision Support & QualityApply segmentation, driver analysis, measurement approaches, scenario testing, predictive techniques, and other methods where they fit the business question.Validate assumptions, document methods, pressure-test conclusions, and ensure outputs are transparent and appropriately caveated.Partner with data science, data engineering, and technology teams to support automation, reusable data products, and tool-enabled delivery.Prepare clear, decision-ready materials for working teams and senior stakeholders, escalating strategic considerations and recommendations.Maintain high standards for accuracy, consistency, compliance with data-use expectations, and business relevance.5. Delivery Discipline, Reuse & Continuous ImprovementStandardize recurring work into reusable methods, templates, and insight products where scale creates value across the .