Senior Data Scientist

Senior Data Scientist About the Role At Hinge Health, we're revolutionizing how users experience physical therapy and fitness by leveraging computer vision technology. Our computer vision platform provides real-time feedback on users' exercise form to ensure they perform exercises with the correct rep ranges and timing, aiming to optimize pain reduction and overall health outcomes. We're seeking a Senior Product Data Scientist to lead the data strategy behind this transformative feature. You'll partner directly with Product and Engineering to drive business strategy through proactive analysis and experimentation. In this role, you will own the computer vision analytics space end-to-end — setting metrics, designing experiments, building predictive models, and shaping the product roadmap through data-driven insights. You will be a critical thought partner to Product and Engineering leadership, driving the future of real-time feedback technology in a growing health-tech company. The ideal candidate is proactive, curious, and able to take ownership of product metrics and data models to shape the next evolution of our computer vision experience. Our stack: Python, SQL, dbt, Mode, Databricks, Airflow, Statsig, AWS What You'll Accomplish - Lead the data strategy for the computer vision platform, driving product decisions that ensure accurate real-time feedback on users' exercise form to optimize pain reduction and health outcomes. - Design, execute, and analyze experiments to continuously improve user outcomes and the overall product experience. - Own and refine data models that power the computer vision experience, from exercise tracking to feedback mechanisms. - Define and monitor key metrics related to exercise form, user engagement, and feedback effectiveness, providing actionable insights to stakeholders and leadership. - Build and maintain self-service data tools, dashboards, and reporting systems that empower product teams to easily access insights from the data and make informed decisions. - Apply machine learning and predictive modeling to anticipate user behaviors, such as identifying patterns that predict whether a user is at risk of poor form or injury. - Drive deep-dive analyses to assess the impact of computer vision features on user outcomes, such as pain reduction, mobility improvement, and exercise compliance. - Lead the definition of data taxonomy and architecture around the computer vision space, ensuring data quality and consistency across teams. - Advocate for upstream data architecture and taxonomy best practices, working closely with Data Engineering to improve downstream data quality. - Partner with product managers and engineers to define the roadmap for new data features, ensuring the product is continually improving and scaling effectively. Basic Qualifications - 5+ years of experience in Data Science, Product Analytics, or related fields. - 5+ years of experience with Python and SQL, with the ability to transform complex data into actionable insights. - Experience designing and analyzing A/B tests and other experimental frameworks. - Proven ability to translate complex data into clear, actionable insights and communicate findings effectively to both technical and non-technical stakeholders. - Experience building dashboards and reports for monitoring product or operational metrics using tools like Mode, Tableau, or similar. - Experience with productionalizing data models and ETL pipelines. Preferred Qualifications - 1+ years of experience with machine learning and predictive modeling. - Bachelor's or Master's degree in a relevant field (Data Science, Computer Science, Engineering, Statistics, etc.). - Prior experience in healthcare, wellness, or digital health environments, particularly in fitness technologies or real-time feedback systems. - Knowledge of cloud infrastructure and tools such as AWS, Databricks, and Airflow. Hinge Health Hybrid Model We believe that remote work a ... (truncated, view full listing at source)