Data Scientist, Hinge Health

• The ideal candidate will be passionate about driving better user outcomes through data and technology and will have experience in product analytics and ML within a user engagement or communications context
• 2+ years of experience as a Data Scientist or in a related role focused on product analytics and machine learning
• 2+ years of experience with Python and SQL, with the ability to transform complex data into actionable insights
• Experience with building and automating reports and dashboards for non-technical stakeholders using tools like Mode, Tableau, or similar
• Experience with productionalizing data models/ETL

Desirable

• At Hinge Health, we are committed to improving the user experience and engagement across our health programs
• As part of our product team, you’ll focus on optimizing post-enrollment communications to help drive user engagement, adherence, and overall success
• These communications span multiple channels, including email, SMS, notifications, and interactions with our care team (Physical Therapists, Coaches, etc.)
• We are seeking a Product Data Scientist to join our Data Science team and work on proactive analysis and experimentation to inform the strategy behind our communications efforts
• This role will include building and owning data models, setting metrics, and working across teams to improve how we engage users and help them stick with their treatment plans
• You’ll be key in optimizing communications for a personalized, timely, and effective experience for our members
• Our stack: Python, SQL, dbt, Mode, Databricks, Airflow, Statsig, AWS
• Work with product, engineering, and care teams to optimize and personalize post-enrollment member communications, driving higher user engagement and adherence
• Design, execute, and analyze experiments to improve user outcomes and the overall product experience
• Develop and maintain data models to evaluate and improve the effectiveness of communication channels (email, SMS, notifications) in terms of user response, engagement, and retention
• Set up and monitor key product metrics (e.g., user engagement, message open rates, conversion to next milestones) to assess the impact of communications on user behavior and outcomes
• Apply machine learning and statistical models to understand and predict user behavior based on past engagement patterns, and use these insights to personalize communication strategies
• Build and deploy anomaly detection systems to identify when communications are underperforming or when there are issues in user engagement
• Collaborate with stakeholders across teams (Product, Marketing, Care Team) to define actionable data insights that guide the design of effective messaging strategies
• Develop self-service tools and dashboards for stakeholders to easily access insights and track the performance of communications campaigns
• Contribute to the creation and optimization of communication content by understanding user response trends, ensuring messages are relevant, timely, and motivating for users
• Drive improvements in data quality, ensuring robust taxonomy and data models that support long-term communications optimization efforts