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Job description
Job Title
Product Data Scientist (Product Analytics / ML)
Salary
Not Disclosed + Equity
Company Description
Peer AI is a Bay Area-founded, venture-backed company transforming drug development with AI-powered intelligence for a $23B addressable market.
Job Description
You will build the feedback system revealing how Peer AI’s product truly performs, analyzing rich signals from AI-agent actions and document-generation workflows. Sitting at the intersection of data science and engineering, you’ll define core health metrics, design durable semantic models, and build automated systems that connect usage signals to customer outcomes.
Location
San Francisco, USA
Why this role is remarkable
Work on a platform already live with top-tier pharma customers, directly accelerating the delivery of life-saving medical treatments to patients.
Join an AI-native engineering culture that prioritizes automation and system-building over recurring manual tasks and one-off reporting.
Receive a meaningful equity grant in a high-growth startup backed by investors with deep roots in technology and life sciences.
What You Will Do
Define core product health metrics and design durable event models for complex entities like AI-agent actions and study documents.
Partner with engineering teams to instrument new capabilities, ensuring high-quality analytics is integrated directly into the feature development process.
Build automated analyses and AI-assisted systems that detect meaningful changes in user behavior and connect signals to downstream outcomes.
The ideal candidate
Possesses excellent SQL and strong Python skills with significant experience in product analytics, data science, or analytics engineering.
Demonstrates comfort working with raw event data and application semantics to fix instrumentation rather than just consuming polished tables.
Brings a strong grounding in funnels, cohorts, and behavioral analysis with the ability to turn ambiguous data into product recommendations.
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Worksite address
san francisco, CA, 94199, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.