Digital Product Manager, Strategy and Innovation

Join Amgens Mission of Serving Patients At Amgen, if you feel like youre part of something bigger, its because you are. Our shared missionto serve patients living with serious illnessesdrives all that we do. Since 1980, weve helped pioneer the world of biotech in our fight against the worlds toughest diseases. With our focus on four therapeutic areas Oncology, Inflammation, General Medicine, and Rare Disease we reach millions of patients each year. Amgen is advancing a broad and deep pipeline of medicines to treat cancer, heart disease, inflammatory conditions, rare diseases, and obesity and obesity-related conditions. As a member of the Amgen team, youll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller happier lives. Our award-winning culture is collaborative, innovative, and science based. If you have a passion for challenges and the opportunities that lay within them, youll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career. Digital Product Strategy and Innovation Manager What You Will Do Lets do this. Lets change the world. We are seeking aDigitalProduct Manager,to join the AI & Data Lab Product Management Team. This role is focused onrapidly validating high-potential AI and data-driven business opportunities before major investment, helping Amgen determine which AI initiatives should be scaled, refined, paused, or redirected. TheDigital Product Manager will operate at the intersection ofbusiness strategy, AI product discovery, data readiness, technical feasibility, experimentation, and enterprise transformation. You will partner closely with business leaders, scientists, data scientists, machine learning engineers, data engineers, software engineers, architects, and functional experts to identify meaningful problems, shape AI-enabled opportunity hypotheses, run fast validation cycles, and generate evidence-based recommendations for investment decisions. This role requires a strong product mindset combined with sufficient technical depth to evaluate whether AI and data opportunities are practical, scalable, measurable, and aligned to Amgens enterprise technology direction. The successful candidate will understand how AI products are built, validated, deployed, monitored, and scaled in complex enterprise environments. Responsibilities Identify, frame, and validate AI-enabled business opportunities across Amgen. Translate broad transformation themes into clear problem statements, testable hypotheses, user needs, data requirements, success metrics, and validation plans. Evaluate whether proposed AI opportunities have the right data foundations, system integrations, architecture patterns, model capabilities, security controls, and operational support needed to move from concept to scalable solution. Collaborate with data scientists, ML engineers, data engineers, software engineers, solution architects, platform teams, and cybersecurity partners to shape solution concepts, understand technical tradeoffs, and identify dependencies early in the validation process. Design and execute rapid discovery sprints, prototypes, pilots, user research, and experiments to assess desirability, feasibility, viability, value, and risk. Use evidence to determine whether opportunities should advance, pivot, pause, or scale. Assess how LLMs, AI agents, machine learning models, NLP, automation, knowledge retrieval, analytics, and intelligent workflow tools can improve productivity, decision quality, scientific discovery, operational efficiency, and workforce effectiveness. Develop product requirements that account for user experience, data availability, model performance, output quality, explainability, reliability, latency, integration needs, governance, and ongoing measurement. Synthesize findings from validation work into clear product recommendations, opportunity briefs, technical feasibility assessments, business cases, and executive-ready narratives. Help leaders make informed decisions about where to invest, scale, or stop. Maintain a portfolio of AI opportunity experiments across stages of discovery, prototype, pilot, and scale-readiness. Track progress, risks, assumptions, evidence, data dependencies, architecture implications, and decision points. Ensure validation efforts consider responsible AI, data privacy, model risk, cybersecurity, compliance, regulatory considerations, human oversight, change management, and enterprise scalability from the earliest stages of discovery. Facilitate workshops, discovery sessions, prioritization discussions, technical feasibility reviews,user experience design, process mapping, and decision forums. Communicate complex AI and data concepts in a clear, business-oriented way for senior leaders and non-technical stakeholders. What we expect of you We are all different, yet we all use our unique contributions to serve patients. The Digital Product Manager professional we seek has these qualifications. Basic Qualifications Doctorate; or Masters degree and 2 years of Information Systems, Technology, Product, Digital, AI, Data, Business Transformation, or related experience;or Bachelors degree and 4 years of Information Systems, Technology, Product, Digital, AI, Data, Business Transformation, or related experience;or Associates degree and 8 years of Information Systems, Technology, Product, Digital, AI, Data, Business Transformation, or related experience;or High School Diploma or GED and 10 years of Information Systems, Technology, Product, Digital, AI, Data, Business Transformation, or related experience. Preferred Qualifications 4+ years of product management, product strategy, innovation, consulting, digital transformation, or related experience. 2+ years of experience with AI, machine learning, data products, automation, LLMs, agents, NLP, analytics, or enterprise AI solutions. Working knowledge of AI product development, including discovery, prototyping, model evaluation, deployment, monitoring, and iteration. Familiarity with generative AI, LLMs, retrieval-augmented generation, AI agents, prompt engineering, model orchestration, NLP, predictive analytics, or intelligent automation. Understanding of data architecture concepts, including data pipelines, data lakes, data warehouses, APIs, metadata, master data, data governance, and data quality. Familiarity with enterprise AI platforms, MLOps, model lifecycle management, responsible AI practices, and AI governance. Ability to partner with technical teams to assess solution architecture, integration complexity, platform fit, security implications, and operational scalability. Experience running product discovery, design thinking, lean startup, rapid prototyping, experimentation, pilots, or proof-of-concept initiatives. Ability to evaluate AI opportunities across desirability, feasibility, viability, value, risk, scalability, and data readiness. Experience developing business cases, opportunity assessments, technical feasibility summaries, executive narratives, or investment recommendations. Familiarity with biotech, pharmaceutical, R&D, manufacturing, medical, or enterprise business workflows. Strong presentation and storytelling skills, including experience communicating technical recommendations to senior leaders. Hands-on ability to analyze user feedback, usage data, workflow metrics, model outputs, experiment results, or AI product performance. Comfort working in fast-paced, cross-functional environments where priorities evolve quickly. What You Can Expect Of Us As we work to develop treatments that take care of others, we also work to care for your professional and personal growth and well-being. From our competitive benefits to our collaborative culture, well support your journey every step of the way. The expected annual salary range for this role in the U.S. (excluding Puerto Rico) is posted