Manager - Commercial Analytics & AI Enablement (Sr Data Scientist)

Career Category
Operations
Job Description
The Commercial Analytics team at Amgen serves as a strategic partner to Commercial leadership. It delivers rigorous analyses and data-driven insights that drive US commercial performance. This role is part of Amgen's growing analytics capability in India. It works closely with US-based Commercial and Global Customer Capabilities Innovation teams to advance how artificial intelligence is applied to insight generation and decision-making across the enterprise.
As Commercial Analytics Manager for AI Innovation & Enablement, you will be accountable for defining and executing the team's AI strategy across the commercial portfolio. You will partner with the leadership to set priorities, govern the delivery of AI solutions, and ensure that each capability creates measurable business value while meeting the highest standards of quality and compliance. You will guide the work of Senior Associates and analysts and act as the primary point of contact for cross-functional AI partnerships. The role requires deep commercial analytics expertise, technical fluency in AI, sound judgment, and the ability to lead change without direct authority.
Live | What you will do
1. AI Strategy, Roadmap & Portfolio Prioritization

- Define and maintain the team's AI roadmap in partnership with the Leadership team, aligning initiatives with US commercial priorities and enterprise AI direction.

- Identify, assess and prioritize cross-portfolio AI use cases based on business value, feasibility, data readiness and risk.

- Translate US business questions into structured AI solution approaches with clear objectives, success criteria and value measures.

- Assess emerging AI technologies, platforms and industry practices, and recommend which to adopt and where.
2. Solution Delivery & Platform Leadership

- Lead end-to-end delivery of AI initiatives, from proof of concept to production, while guiding Senior Associates and analysts on design, build and execution.

- Shape a reusable AI platform and asset library, including agents, prompt frameworks, code modules and workflow accelerators, that can scale across brands and teams.

- Work with Information Systems, data engineering and platform teams to connect AI solutions to governed commercial data sources such as claims, specialty pharmacy, CRM and other secondary data.

- Ensure solutions are documented, maintainable and set up for long-term ownership and handover.
3. Quality, Governance & Responsible AI

- Establish and own the quality framework for AI-enabled analytics, covering validation standards, evaluation methods, human-in-the-loop review and ongoing performance monitoring.

- Ensure that AI-generated insights are accurate, reproducible, traceable to source data, and fit for use by senior stakeholders.

- Ensure all AI work complies with Amgen's responsible AI principles, data privacy requirements, and applicable legal, regulatory and compliance SOPs across internal teams and vendor partners.

- Proactively identify and mitigate risks associated with AI solutions, including model reliability, bias and data security.
4. Stakeholder Leadership, Adoption & Capability Building

- Serve as the primary AI partner to US teams across brand analytics, forecasting, and market research

- Communicate AI strategy, progress and impact to senior stakeholders through concise narratives and visuals.

- Drive AI adoption across the analytics organization through structured enablement programs, playbooks, training and knowledge-sharing forums.

- Define and report metrics for adoption, productivity gains and business impact.

- Build AI capability within the India team by coaching and developing team members and fostering a culture of curiosity, experimentation, accountability, inclusion and continuous improvement.
Thrive | What you can expect
As we work to develop treatments that take care of others, we also work to care for our teammates' professional and personal growth and well-being.
Basic Qualifications

- Bachelor's degree with 8–13 years, or Master's degree with 6 years, of relevant experience in analytics, data science or sales and marketing operations.

- Proven experience leading the design and delivery of AI, machine learning or advanced analytics solutions into production.

- Strong proficiency in Python, JS, AI development with hands-on experience in generative AI and LLM applications such as prompt engineering, retrieval-augmented generation (RAG), agentic workflows and API integration.

- Working knowledge of cloud data platforms (AWS, Databricks) and visualization tools such as Tableau.

- Exposure to US commercial pharmaceutical secondary data sources and commercial performance measurement frameworks.
Preferred Qualifications

- Demonstrated success in driving enterprise adoption of AI or analytics tools across cross-functional, multi-geography teams.

- Experience establishing quality, validation or governance frameworks for AI or analytical outputs.

- Familiarity with enterprise AI platforms, AI coding assistants, MLOps/LLMOps practices and software engineering standards (version control, code review, documentation).

- Ability to assess the strengths, limitations and risks of different AI and analytical approaches and make sound trade-offs.

- Proven ability to influence senior stakeholders and lead cross-functional initiatives without direct authority.

- Experience mentoring or leading analysts and building team capability.

- Exceptional written and verbal communication skills, with the ability to convey complex technical concepts as a compelling, concise narrative for executive audiences.

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