Product Data Scientist (Product Analytics / ML)

Getpeer; San Francisco, Northern (CA, KY); Hybrid; USD 150,000 - 210,000; Full time

Benefits offered by this job

Equity grant

Remote-first with SF on-sites

Health coverage

Parental leave (12 weeks)

Home-office stipend

Unlimited PTO

Job summary

Peer AI in the Bay Area seeks a Senior Product Data Scientist to lead product analytics and ML efforts. You will define the core metrics for activation, engagement, retention, and outcomes, and partner with engineering to instrument capabilities.

You will build trustworthy data models, analyze complete user journeys, and create automated analyses that connect usage signals to AI quality and customer outcomes.

Qualifications

• Excellent SQL and strong Python skills.
• Experience in product analytics, data science, analytics engineering, or a role spanning those disciplines.
• Comfort working with raw event and application data, defining semantics, and fixing instrumentation.
• Strong grounding in funnels, cohorts, retention, experimentation, and behavioral analysis.
• Ability to turn ambiguous analysis into clear product recommendations, with a bias toward reusable data products and automated insight loops.

Responsibilities

• Define the core metrics for product health, activation, adoption, engagement, retention, and successful customer outcomes.
• Design a durable event and semantic model for complex entities such as organizations, studies, documents, sources, generation operations, and AI-agent actions.
• Partner with engineers to instrument new capabilities so analytics is part of feature development rather than an afterthought.
• Build trustworthy analytical datasets and connect product behavior with operational, quality, and AI-system data.
• Analyze complete user journeys to identify where customers succeed, struggle, abandon workflows, regenerate content, or require additional support.
• Build automated analyses and AI-assisted systems that detect meaningful changes and connect usage signals to AI quality and downstream customer outcomes.

Skills

SQL

Python

Product analytics

Data science

Instrumentation

Funnels & cohorts

Experimentation

Communication of insights

Job description

Product Data Scientist (Product Analytics / ML)

Full-Time, Bay Area, Hybrid

Location: Bay Area / Hybrid

Type: Full-Time

Level: Senior / Staff

Why this role is exciting

Build the feedback system that tells us how the product is really working. Peer AI produces far richer signals than a typical SaaS product: user behavior, document-generation operations, source relationships, AI-agent actions, edits, quality measures, retries, failures, and workflow outcomes. You will sit at the intersection of product analytics, data science, and engineering - deciding what to measure, making the data trustworthy, and building systems that proactively surface what changed, why it matters, and where users are succeeding or struggling.

About Peer AI

We're a Bay Area-founded, remote-friendly company backed by investors with deep roots in both technology and life sciences. Our platform is live with top-tier pharma customers today, and we're growing fast in a $23B addressable market spanning document authoring, submission workflow management, and agency interactions with the FDA and EMA.

Our Vision

At Peer AI, we are working to clear the path for important scientific and medical discoveries, so that treatments reach the patients who need them as quickly as possible.

Our Values

• Drive Impact: We focus on delivering real results for our users. Making their work easier, better, and more impactful.




• Be the Expert: We lead with deep expertise, curiosity, and honesty to guide others toward the best outcomes.




• Go for Great: We take pride in pushing past "good enough" to deliver standout work in every detail.




• Win as a Team: We succeed together—building trust, sharing ownership, and helping each other grow every day.

How We Work

Peer AI is an AI-native company, and we want our engineering organization to be AI-native too. We use AI throughout how we build, test, analyze, debug, and operate software. We look for people who ask what can be automated, what should become a system instead of a recurring task, and where human judgment creates the most value. These roles are intentionally broader than their traditional equivalents because we want the people who join us to help redefine the function itself.

KeyResponsibilities

• Define the core metrics for product health, activation, adoption, engagement, retention, and successful customer outcomes.




• Design a durable event and semantic model for complex entities such as organizations, studies, documents, sources, generation operations, and AI-agent actions.




• Partner with engineers to instrument new capabilities so analytics is part of feature development rather than an afterthought.




• Build trustworthy analytical datasets and connect product behavior with operational, quality, and AI-system data.




• Analyze complete user journeys to identify where customers succeed, struggle, abandon workflows, regenerate content, or require additional support.




• Build automated analyses and AI-assisted systems that detect meaningful changes and connect usage signals to AI quality and downstream customer outcomes - not just clicks, but whether the product accomplished the user's goal.

Must-HaveQualifications

• Excellent SQL and strong Python skills.




• Experience in product analytics, data science, analytics engineering, or a role spanning those disciplines.




• Comfort working with raw event and application data, defining semantics, and fixing instrumentation rather than only consuming polished BI tables.




• Strong grounding in funnels, cohorts, retention, experimentation, and behavioral analysis.




• Ability to turn ambiguous analysis into clear product recommendations, with a bias toward reusable data products and automated insight loops instead of repeated one-off analysis.

Nice-to-Have

• Experience applying ML to anomaly detection, clustering, recommendation, behavioral analysis, or unstructured data.




• Experience analyzing AI/agent systems, evaluation data, or human interaction with generated content.




• Experience with complex B2B SaaS, healthcare, life sciences, or another domain where a successful workflow matters more than raw click volume.

WhatWeOffer

• Meaningful equity grant in a high-growth, venture-backed company.




• Remote-first setup with quarterly on-sites in San Francisco.




• Comprehensive health coverage, 12 weeks paid parental leave, and monthly home-office stipends.




• Unlimited PTO and a mission that directly accelerates life-saving clinical research.

Equal Opportunity

Peer AI is an equal opportunity employer. We consider qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, genetic information, or any other characteristic protected by applicable law. If you need a reasonable accommodation during the hiring process, please let us know.

Hiring Manager

Head of Engineering