Staff Machine Learning Scientist

About the RoleHinge 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 AccomplishSend-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 QualificationsAt minimum, a Bachelor's degree or higher in Computer Science, Statistics, Operations Research, Machine Learning, or a related quantitative fieldAt minimum 4 + years building and deploying ML systems in production at consumer scaleAt least one recommendation, ranking, or sequential-decisioning system shipped end-to-end (modeling, evaluation, deployment, monitoring, iteration)Fluency in experimentation and A/B testing: multi-arm tests, sequential testing, CUPED, and the common failure modes of online experimentsProficiency in Python and SQL; able to read a colleague's PR and improve itDeep understanding of machine learning and applied statisticsPreferred Qualifications7+ years building and deploying ML systems in production at consumer scaleContextual bandits or reinforcement learning operated in productionMulti-objective optimization (engagement vs. adherence vs. retention vs. cost)Causal inference beyond A/B testing: difference-in-differences, synthetic controls, instrumental variablesCold-start and low-data-regime modeling (healthcare gets thin on per-member data fast)Experience hiring and growing a small ML teamHealthcare, fintech, or other regulated-data experience; familiarity with HIPAA and BAA constraintsFamiliarity with our adjacent stack: Statsig, Databricks, feature stores, Airflow/dbtFamiliarity with TypeScriptAbout Hinge HealthHinge Health leverages software, including AI, to largely automate care for joint and muscle health, delivering an outstanding member experience, improved member outcomes, and cost reductions for its clients. The company has designed its platform to address a broad spectrum of MSK care—from acute injury, to chronic pain, to post-surgical rehabilitation—and the platform can help to ease members’ pain, improve their function, and reduce their need for surgeries, all while driving health equity by allowing members to engage in their exercise therapy sessions from anywhere. The company is headquartered in San Francisco, California.Learn more atWhat You'll Love About UsInclusive healthcare and benefits: On top of comprehensive medical, dental, and vision coverage, we offer employees and their family members help with gender-affirming care, tools for family and fertility planning, and travel reimbursements if healthcare isn’t available where you live.Planning for the future: Start saving for the future with our traditional or Roth 401k retirement plan options which include a 2% company match.Modern life stipends: Manage your own learning and developmentCulture & EngagementHinge Health is an equal opportunity employer and prohibits discrimination and harassment of any kind. We make employment decisions without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, age, veteran status, disability status, pregnancy, or any other basis protected by federal, state or local law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. We provide reasonable accommodations for candidates with disabilities. If you feel you need assistance or an accommodation due to a disability, let us know by reaching out to your recruiter.By submitting your application you are acknowledging we are using your personal data asoutlined in the personnel and candidate privacy policy.Beware of Phishing Attempts: We've noticed an increase in phishing where fraudsters impersonate employees and send fake job offers to steal sensitive information. We'll never ask for financial details during the hiring process and only use "@hingehealth.com" emails. If you receive a suspicious offer, stop communication and report it to the US FBI Internet Crime Complaint Center. To verify an email from our recruiting team, forward it to View email address on click.appcast.io Range: $204,608 - $306,912LocationSan Francisco-HQEmployment TypeFull timeLocation TypeHybridDepartmentRnDEngineeringCompensationtier1$204,608 – $306,912 • Offers EquityThis position will have an annual salary, plus equity and benefits. Please note the annual salary range is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, and competencies.