Hinge Health

Healthcare

StaffMachineLearningScientist

$205–307k San Francisco, California, United States FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Staff Machine Learning Scientist at Hinge Health. Skills: Machine Learning, Data Engineering, Business Intelligence, Analytics. Develop and deploy machine learning models. Design and implement data pipelines”

Industry & Context.

Healthcare

What They're Looking For.

Must Have

7+ years of experience

Nice to Have

PhD preferred, Specific ML framework experience, Cloud platform certs

What You'll Do.

Develop and deploy machine learning models

Design and implement data pipelines

Build and maintain BI dashboards

Perform quantitative analysis

Collaborate with engineering teams

Drive data-informed decisions

Stay current with ML/AI advancements

How You'll Work.

Team & Collaboration

Cross-functional teams

Full Job Description

ABOUT THE ROLE Hinge Health helps people move without pain through digital musculoskeletal (MSK) care. That care only works when members keep doing their exercise therapy, and the right message at the right moment is a large part of what keeps them going. As a Staff ML Scientist on the Proactive Communications & Notifications team at Hinge Health, you'll own the machine learning that decides what message each member receives, when, and through which channel. At our scale, small gains in relevance and timing compound into large gains in engagement and clinical outcomes. You'll be the technical leader for ML on the team: setting direction for send-time optimization, propensity modeling, and the experimentation rigor behind every nudge we ship. You'll write code your senior engineers respect, mentor a small ML team, and partner closely with product, data science, and our growth and marketing teams. Our ideal candidate has shipped recommendation or sequential-decisioning systems that changed how real users behave, runs experiments with rigor, and writes code their engineers respect. They optimize for what moves for members, not model sophistication for its own sake.   WHAT YOU'LL ACCOMPLISH - Send-time and channel optimization: Design and ship the next system for deciding what nudge to send a member, when, and through which channel, beyond our current contextual-bandit approach. - Propensity modeling: Build and deploy models that decide whether nudging a given member is worth it, balancing engagement against fatigue and unsubscribes. - Experimentation rigor: Set the bar for how the team runs experiments: multi-arm tests, sequential testing, CUPED, and guarding against peeking, so our nudge decisions are causally sound. - Production ownership: Own at least one model in production end-to-end. - Leadership: Mentor the team's ML scientists, guide technical direction, and partner across product, engineering, data science, and the growth and marketing teams. REQUIRED QUALIFIC

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