Senior Digital Product Strategy and Innovation Manager (AI)

Amgen

Confirmed live yesterday High trust
Remote

Quick summary

Work type
Remote
Location
Jacksonville, FL
Salary
$170,958–$231,297 / yr
Employment
Full-time
Posted
4 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $209k
This role $201k
$155k $249k
below market most similar roles pay here above market

This role pays more than 52% of similar roles. Most pay $177,250–$240,037 — the blue band above. At the midpoint, this role pays about $201k versus about $209k for comparable roles.

Based on 240 similar postings.

Employer

About Amgen

Amgen is a leading biotechnology company that discovers, develops, manufactures, and delivers innovative human therapeutics, with products addressing conditions such as anemia, bone loss, inflammation, and cancer. Industry: Biotechnology & Pharmaceuticals

Amgen currently has 66 open roles on FindRole.

Listed pay typically runs $156,190–$211,315 across 45 roles with salary data.

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View all roles at Amgen

At a glance

TL;DR · Senior Digital Product Strategy and Innovation Manager (AI)

The Senior Digital Product Strategy and Innovation Manager (AI) joins the AI & Data Lab Product Management Team to lead the identification, evaluation, and validation of high-potential AI and data-driven opportunities. This role involves shaping strategic opportunities, providing evidence-based recommendations for enterprise investment, and establishing product discovery approaches to determine where AI creates meaningful business and patient value. You will collaborate with data scientists, ML engineers, and cybersecurity partners to assess LLMs, AI agents, machine learning models, NLP, and automation tools. Key responsibilities include designing rapid discovery sprints, prototypes, and pilots to evaluate feasibility, risk, and scalability. You will synthesize findings into technical feasibility assessments and executive narratives, ensuring that all initiatives account for data privacy, model risk, governance, and enterprise scalability within a complex biotech environment.

What you'll do

  • Identify, frame, and prioritize AI-enabled business opportunities to ensure alignment with enterprise strategic goals.
  • Evaluate AI opportunities for data foundations, system integrations, architecture patterns, security controls, and operational support.
  • Design and execute rapid discovery sprints, prototypes, pilots, and user research to assess feasibility and risk.
  • Develop product requirements covering user experience, model performance, explainability, governance, and integration needs.
  • Synthesize validation findings into clear product recommendations, business cases, and executive-ready narratives for senior leadership.
  • Manage a portfolio of AI opportunities across discovery, prototype, pilot, and scale-readiness stages.
  • Lead cross-functional decision forums to align business, scientific, technology, and security stakeholders on product direction.
  • Provide coaching and thought leadership to product managers to improve AI discovery and experimentation practices.

What we're looking for

  • Must meet one of the following: Doctorate with 2 years, Master’s with 6 years, Bachelor’s with 8 years, Associate’s with 10 years, or High school diploma/GED with 12 years of relevant experience.
  • Must have a minimum of 2 years of experience directly managing people or leading teams, projects, programs, or directing resource allocation.
  • Relevant experience must be in Information Systems, Technology, Product, Digital, AI, Data, Business Transformation, or a related field.
  • 4+ years of experience in product management, product strategy, innovation, consulting, or digital transformation (preferred).
  • 2+ years of experience with AI, machine learning, data products, automation, LLMs, agents, NLP, analytics, or enterprise AI solutions (preferred).
  • Demonstrated experience leading AI or data products through discovery, validation, investment decision, and scale (preferred).
  • Understanding of data architecture concepts including pipelines, lakes, warehouses, APIs, metadata, governance, and data quality (preferred).
  • Familiarity with biotech, pharmaceutical, R&D, manufacturing, medical, or enterprise business workflows (preferred).

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