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About This Role
What if the work you did every day could impact the lives of people you know? Or all of humanity?
At Illumina, we are expanding access to genomic technology to realize health equity for billions of people around the world. Our efforts enable life\-changing discoveries that are transforming human health through the early detection and diagnosis of diseases and new treatment options for patients.
Working at Illumina means being part of something bigger than yourself. Every person, in every role, has the opportunity to make a difference. Surrounded by extraordinary people, inspiring leaders, and world changing projects, you will do more and become more than you ever thought possible.
This role sits within Global Operations Analytics (GOA) and supports the Supply Chain analytics pod, with a primary focus on Delivery (Deliver), including Transportation, Logistics, Packaging, Global Trade, and Order\-To\-Ship (O2S) processes. The role focuses on Supply Chain Analytics and Business Intelligence (BI), leveraging data modeling, SQL\-based analysis, AI, and data visualization to deliver scalable, insight\-driven solutions.
The position serves as a US\-based, customer\-facing analytics lead for the Delivery pillar, partnering directly with Supply Chain stakeholders to drive strategic initiatives and improve operational performance. The role also collaborates closely with Supply Chain Product Managers and cross\-functional teams across Quality, Facilities, and Asset Lifecycle Management to ensure alignment of analytics solutions with broader Global Operations priorities.
This role operates with a data product manager mindset, owning the vision and roadmap for analytics solutions and defining how business problems should be solved through scalable data products (e.g., dashboards, workflows, or AI\-enabled solutions). The focus is on delivering insight\-driven outcomes and enabling data\-informed decision\-making.
Key Responsibilities:
- Serve as the primary US\-based analytics lead for the Delivery (Deliver) pillar, acting as the main point of contact for business stakeholders.
- Lead the definition, prioritization, and execution of analytics initiatives aligned to Delivery, including logistics, transportation, packaging, global trade, service levels, and lead times.
- Own the vision and roadmap for Delivery analytics data products, translating business needs into scalable solutions (dashboards, workflows, or AI\-enabled capabilities).
- Drive a shift from reporting to insight\-driven analytics by identifying trends, root causes, and actionable opportunities for operational improvement.
- Partner with senior stakeholders and Supply Chain Product Managers to support strategic initiatives and ensure alignment across domains.
- Apply strong SQL and data modeling principles to analyze complex datasets and support scalable data architecture and reporting solutions.
- Design and develop scalable Business Intelligence (BI) and analytics solutions leveraging Tableau, Snowflake, SAP HANA, and modern data architecture principles.
- Collaborate with data engineering teams and contribute to development of semantic data layers in Snowflake to support consistent and scalable reporting.
- Coordinate with global (including India\-based) analytics resources to execute against priorities and scale delivery.
- Ensure analytics outputs are aligned to business definitions, scalable, and focused on delivering measurable business impact.
- Communicate insights and recommendations clearly to both technical and non\-technical audiences.
- Drive adoption and sustained usage of analytics solutions across stakeholders.
Qualifications:
- 8\+ years of experience in analytics, business intelligence, or data product\-related roles.
- Experience supporting Supply Chain analytics, with exposure to Delivery (Deliver), logistics, transportation, packaging, or global trade processes.
- Experience operating with a data product mindset, including defining problem statements, prioritizing work, and delivering scalable analytics solutions aligned to business outcomes.
- Strong experience with SQL and working with large\-scale datasets.
- Strong experience with Tableau for data visualization and dashboard development (preferred).
- Experience working with Snowflake and/or SAP HANA for data analysis and reporting.
- Experience partnering with data engineering teams or contributing to semantic layer/data model development in Snowflake.
- Strong ability to translate business problems into scalable data solutions and actionable insights.
- Excellent stakeholder management and communication skills, with experience engaging cross\-functional and senior business partners.
Preferred Qualifications:
- Experience with data modeling, data architecture, or building scalable semantic layers
- Experience leveraging AI or advanced analytics capabilities (e.g., Snowflake Cortex or similar tools) to enhance decision\-making.
- Exposure to Power BI and/or Databricks.
- Experience in life sciences, manufacturing, or other complex operational\-driven industries (e.g., supply chain, logistics) is a plus.
The estimated base salary range for the Supply Chain Analytics \& AI Product Manager – Global Delivery \& Trade role based in the United States of America is: $118,200 \- $177,200\. Should the level or location of the role change during the hiring process, the applicable base pay range may be updated accordingly. The range reflects long‑term growth in the role. Most candidates are hired between the minimum and middle of the range. Placement depends on experience, skills, location, and internal equity. Additionally, all employees are eligible for one of our variable cash programs (bonus or commission) and eligible roles may receive equity as part of the compensation package. We offer a wide range of benefits as innovative as our work, including access to genomics sequencing, family planning, health/dental/vision, retirement benefits, and paid time off.
We are a company deeply rooted in belonging, promoting an inclusive environment where employees feel valued and empowered to contribute to our mission. Built on a strong foundation, Illumina has always prioritized openness, collaboration, and seeking alternative perspectives to propel innovation in genomics. We are proud to confirm a zero\-net gap in pay, regardless of gender, ethnicity, or race. We also have several Employee Resource Groups (ERG) that deliver career development experiences, increase cultural awareness, and offer opportunities to engage in social responsibility. We are proud to be an equal opportunity employer committed to providing employment opportunity regardless of sex, race, creed, color, gender, religion, marital status, domestic partner status, age, national origin or ancestry, physical or mental disability, medical condition, sexual orientation, pregnancy, military or veteran status, citizenship status, and genetic information. Illumina conducts background checks on applicants for whom a conditional offer of employment has been made. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable local, state, and federal laws. Background check results may potentially result in the withdrawal of a conditional offer of employment. The background check process and any decisions made as a result shall be made in accordance with all applicable local, state, and federal laws. Illumina prohibits the use of generative artificial intelligence (AI) in the application and interview process. If you require accommodation to complete the application or interview process, please contact [email protected]. To learn more, visit: https://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf. The position will be posted until a final candidate is selected or the requisition has a sufficient number of qualified applicants. This role is not eligible for visa sponsorship.
Salary Context
This $118K-$177K range is in the lower quartile for AI Product Manager roles in our dataset (median: $189K across 161 roles with salary data).
View full AI Product Manager salary data →Role Details
About This Role
AI Product Managers define what AI features get built and why. They translate business problems into ML-solvable tasks, work with engineering to scope model requirements, and own the metrics that determine if an AI feature is working. The role requires a rare combination of technical fluency and product instinct.
Unlike traditional product management, AI PM work involves managing uncertainty at a fundamental level. Your model might work 90% of the time. What happens the other 10%? What's the user experience when the AI is wrong? How do you measure 'good enough' for a probabilistic system? These questions don't have easy answers, and the AI PM is the person responsible for finding them.
Across the 3,823 AI roles we're tracking, AI Product Manager positions make up 5% of the market. At Illumina, this role fits into their broader AI and engineering organization.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
What the Work Looks Like
A typical week includes: reviewing model evaluation results with the ML team, defining success metrics for a new AI feature, conducting user research on how customers respond to AI-generated outputs, writing product requirements that include accuracy thresholds and fallback behaviors, and presenting the AI roadmap to leadership. You're the translator between technical capability and business value.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
Skills Required
Technical fluency with ML concepts is essential, though you won't be writing models. Expect to understand training data, evaluation metrics, model limitations, and responsible AI practices. SQL and basic Python are increasingly expected. Experience with A/B testing, data analysis, and product analytics is baseline. Understanding LLM capabilities and limitations is now a core requirement.
The differentiator is AI-specific product thinking: knowing when to use ML vs. heuristics, understanding the cost of training data collection, designing graceful degradation for model failures, and building products that improve with usage data. Experience with AI safety, bias mitigation, and responsible AI deployment is increasingly important.
Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
Compensation Benchmarks
AI Product Manager roles pay a median of $213,800 based on 583 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,000. This role's midpoint ($147K) sits 31% below the category median. Disclosed range: $118K to $177K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Illumina AI Hiring
Illumina has 2 open AI roles right now. They're hiring across AI Product Manager. Based in San Diego, CA, US. Compensation range: $122K - $177K.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 median).
Career Path
Common paths into AI Product Manager roles include Product Manager, Data Analyst, Technical Program Manager.
From here, career progression typically leads toward Director of AI Product, VP Product, Head of AI.
The most effective path is PM experience plus self-directed AI education. Take Andrew Ng's courses, build a small ML project, and learn enough Python to read model evaluation code. The goal isn't to become an ML engineer. It's to have credibility in technical conversations and to understand what's possible, what's hard, and what's a bad idea.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
AI Hiring Overview
The AI job market has 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 roles).
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
The AI Job Market Today
The AI job market spans 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (112) are outnumbered by mid-level (1,798) and senior (1,516) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $275,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
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