Career Category
Information Systems
Job Description

Digital AI Product Analyst

What you will do

Let's do this. Let's change the world. The Digital AI Product Analyst, AI Studio position offers a unique opportunity to join a fun, innovative team within the AI & Data Science organization. This role will support next-generation AI, automation, process intelligence, digital workflow, and productivity capabilities across Amgen's AI Studio portfolio.

The job offers a unique opportunity to join a fun, innovative engineering team within the AI & Data Science (AI&D) - organization. We are the Applied AI team (AI Studio). AI Studio is Amgen's enterprise engine for turning high-value business challenges into scalable AI products. We partner with key business partners across the company to identify the right opportunities, shape them into actionable use cases, and design, build, and launch AI products responsibly. Our work spans the full lifecycle-from early discovery and rapid prototyping to production deployment, reuse across the enterprise, and measurable business impact.

AI Studio is responsible for the end-to-end lifecycle of enterprise AI products and solutions, including discovery, experience and solution design, development, DevOps, deployment, adoption, and value realization.

The portfolio includes full-stack digital solutions and agentic AI solutions leveraging technologies such as UiPath, large language models, machine learning, Databricks, AWS services, GitLab, Custom GPTs, Claude, and other emerging AI and automation technologies.

The Digital AI Product Analyst will support the analysis, design, development, delivery, and ongoing improvement of AI Studio products and solutions. This role will help connect business needs, user experience, product strategy, and technical delivery by partnering with business stakeholders, Product Managers, designers, architects, engineers, data scientists, platform owners, and external vendors.

The role will translate business needs and user challenges into clearly defined product requirements, user stories, process documentation, data requirements, acceptance criteria, implementation plans, and measurable success outcomes. The Specialist will contribute across the product lifecycle-from initial discovery and solution definition through development, testing, deployment, adoption, operational support, and value realization.

The Digital AI Product Analyst will lead requirements-gathering and user-story development sessions, support product backlog management, analyze data and business processes, coordinate user acceptance testing, and assist with product releases and production deployment. The role will help ensure product decisions are aligned with business priorities, user needs, technical feasibility, scalable architecture, measurable value, and applicable quality, security, privacy, and compliance requirements.

The successful candidate will apply strong business analysis, product analysis, data analysis, and stakeholder-management capabilities to help deliver scalable digital and AI-enabled solutions. The role will support the development of full-stack applications, agentic AI solutions, GenAI applications, machine-learning capabilities, data integrations, enterprise data products, intelligent automation, and digital workflows that improve business processes and user experiences.

Roles & Responsibilities:

• Lead product discovery, requirements-elicitation, process-analysis, and user-story development sessions with business stakeholders, Product Managers, subject matter experts, designers, architects, engineers, data teams, platform owners, and delivery partners.
• Translate business needs and user challenges into clear, development-ready artifacts, including opportunity statements, product requirements, epics, features, user stories, acceptance criteria, process flows, functional requirements, and data requirements.
• Facilitate backlog-refinement and requirements-review sessions to ensure work is clear, complete, testable, technically feasible, and aligned with product strategy and business priorities.
• Maintain and support prioritization of the product backlog based on business value, strategic alignment, user impact, risk, dependencies, delivery readiness, and technical considerations.
• Partner with Product Managers, Delivery Leads, and technical teams to support roadmap planning, sprint planning, release planning, dependency management, and delivery execution.
• Analyze current-state and future-state processes to identify inefficiencies, manual activities, process and data gaps, business rules, risks, and opportunities for AI, automation, digital workflow, or process improvement.
• Support product and solution discovery by documenting business problems, stakeholder needs, user personas, pain points, desired future states, assumptions, risks, dependencies, success measures, and value drivers.
• Support experience and solution design by translating user and business needs into functional workflows, product capabilities, process designs, data interactions, and solution requirements.
• Perform data analysis and execute SQL queries across large datasets to validate requirements, define business logic and metrics, assess data quality, investigate issues, support testing, and inform product decisions.
• Partner with subject matter experts and data owners to define and align metric definitions, data sources, calculations, data usage, and data-quality expectations.
• Collaborate with architects, developers, AI and machine-learning engineers, data scientists, data engineers, automation developers, UX designers, and platform teams throughout the development lifecycle.
• Support the development and delivery of full-stack applications, GenAI applications, agentic AI solutions, machine-learning capabilities, intelligent automation, digital workflows, data integrations, and enterprise data products.
• Support solutions leveraging technologies such as UiPath, large language models, Databricks, AWS services, GitLab, Custom GPTs, Claude, APIs, web-development frameworks, and related AI, automation, cloud, and data platforms.
• Engage with vendors and platform owners to evaluate functionality, technical constraints, integration options, licensing considerations, and opportunities to leverage existing enterprise technologies.
• Coordinate user acceptance testing, including test scenarios, test cases, expected results, test data, requirements traceability, defect documentation, retesting, and business approval.
• Support defect management, production deployment, and DevOps activities, including triage, tracking, business and environment readiness, release coordination, implementation planning, validation, and stakeholder communications.
• Support product operations by monitoring product usage, system performance, incidents, enhancement requests, user feedback, data-quality concerns, and operational support needs.
• Drive adoption and value realization through user guidance, training, demonstrations, communications, adoption measures, business outcomes, value metrics, and post-deployment analysis.
• Create leadership-ready summaries and presentations covering business needs, product recommendations, scope, benefits, risks, dependencies, delivery progress, adoption, and realized value.
• Use approved AI and GenAI tools to improve analysis and documentation while ensuring product activities comply with applicable Amgen quality, security, privacy, responsible AI, data-governance, and regulatory requirements.

What we expect of you

We are all different, yet we all use our unique contributions to serve patients. The professional we seek is an individual with these qualifications.

Basic Qualifications:

Doctorate degree

OR

Master's degree and 2 years of Computer Science, IT or related field

OR

Bachelor's degree and 4 years of Computer Science, IT or related field

OR

Associate's degree and 8 years of Computer Science, IT or related field

OR

High school diploma / GED and 10 years of Computer Science, IT or related field

Preferred Qualifications:

Functional Skills

Must-Have Skills:

• Experience eliciting, analyzing, documenting, validating, and translating business requirements for software, data, digital, AI, automation, or technology implementation initiatives.
• Experience translating stakeholder needs into epics, features, user stories, acceptance criteria, process flows, functional requirements, data requirements, and development-ready documentation.
• Experience applying Agile methodologies and supporting backlog refinement, sprint planning, user-story development, defect management, release planning, and epic tracking.
• Experience using Jira, GitLab, or similar product-development platforms to manage requirements, user stories, defects, dependencies, releases, and delivery activities.
• Experience performing data analysis to define, validate, and document business logic, key metrics, data requirements, testing outcomes, and product-performance measures.
• Ability to write and execute SQL queries against large datasets to validate requirements, investigate issues, assess data quality, and support testing.
• Experience coordinating user acceptance testing, including test scenarios, test cases, expected results, test data, defect documentation, retesting, and business approval.
• Experience supporting production deployment, business readiness, release coordination, stakeholder communication, operational transition, and release management.
• Strong understanding of the product and software-development lifecycle, including design, requirements, development, testing, deployment, adoption, operations, and value realization.
• Ability to analyze business processes and identify opportunities for AI, automation, digital workflow, data, system, or process improvement.
• Experience partnering across business, product, design, architecture, engineering, data, AI, platform, operations, and vendor teams to align requirements, priorities, testing, and delivery decisions.
• Strong communication, analytical thinking, structured problem-solving, and attention to detail, with the ability to independently manage multiple priorities and resolve complex product, technical, process, or data issues in a matrixed environment.

Soft Skills and Behaviors

Must-Have Behaviors:

• Applies structured, evidence-based thinking by asking thoughtful questions, validating assumptions, analyzing available information, and using facts to guide product recommendations and delivery decisions.
• Demonstrates integrity and sound judgment when handling business information, product requirements, stakeholder input, value assumptions, data, and sensitive technical details.
• Focuses on delivering measurable value for patients, staff, business stakeholders, and product users.
• Builds trust through active listening, transparency, respectful challenge, collaboration, and reliable follow-through.
• Communicates clearly and collaborates effectively across business, product, design, architecture, engineering, data, vendor, leadership, and global teams.
• Simplifies complex or ambiguous business and technical needs into clear requirements, user stories, process flows, data logic, and actionable recommendations.
• Takes accountability for the quality, completeness, traceability, and accuracy of product-analysis deliverables.
• Operates with urgency while maintaining appropriate quality, compliance, ethics, privacy, security, scalability, operational readiness, and risk awareness.
• Demonstrates curiosity, continuous learning, and adaptability as technologies, product priorities, stakeholder expectations, user needs, and delivery constraints evolve.

Professional Certifications

• Business Analysis certification, such as CBAP, CCBA, ECBA, or Agile Business Analysis
• SAFe, Scrum Product Owner, or Scrum Master certification
• Product Management certification
• AWS, Databricks, UiPath, or related technology certification
• AI, GenAI, machine learning, automation, or digital-transformation certification
• Data Analytics or Data Management certification
• DevOps, GitLab, or Lean Six Sigma certification

Success Measures:

• Clear, complete, testable, and development-ready requirements, user stories, acceptance criteria, process flows, data definitions, and product documentation.
• Product backlogs and delivery priorities aligned with business value, strategic objectives, user needs, risk, dependencies, and technical feasibility.
• Strong cross-functional alignment across business, product, design, architecture, data, engineering, testing, DevOps, operations, and external partners.
• Effective testing, release readiness, deployment, and operational transition, resulting in fewer requirement gaps, defects, delays, and instances of rework.
• Increased product adoption through effective stakeholder engagement, training, communications, user guidance, usage monitoring, and post-release support.
• Measurable value realization demonstrated through improved productivity, process performance, user experience, data quality, cycle ti