Data Science Manager

About the Role

At Hinge Health, we are building a "coherent platform" that seamlessly integrates digital and hybrid care to move people beyond pain. We are seeking a Manager, Data Science to lead the data strategy for two critical areas of our business:
Treatment Experience and Hinge Select.

In this role, you will own the data roadmap for our most innovative clinical technologies—including Computer Vision (Motion Insights), the Enso wearable device, and our Rewards & Insights (RAIN) engagement platform. Additionally, you will lead the analytics strategy for Hinge Select, our fast-growing hybrid care offering that connects members with virtual specialists and in-person providers.

You will manage and grow a team of high-performing Data Scientists, guiding them to build scalable data products, design rigorous experiments, and deliver insights that shape product direction. You will partner closely with Product, Engineering, and Design leadership to ensure our data infrastructure (taxonomy, data models, and instrumentation) matures alongside our features. This is a high-impact role for a player-coach who thrives in both 0-to-1 product launches (Hinge Select) and the optimization of established, FDA-cleared technologies (Enso, CV).

• Team Leadership & Development:
  Manage, mentor, and grow a team of Data Scientists (currently 4 direct reports). Foster a culture of technical excellence, autonomy, and “radical candor.” You will be responsible for their performance management, career growth, and project prioritization.

• Strategic Thought Partnership:
  Serve as the primary data partner for the Treatment Experience and Hinge Select leadership teams. You will move beyond “service-desk” analytics to proactively identify opportunities (e.g., how to increase CV adoption, optimize Enso utilization, or improve Hinge Select funnel conversion).

• Product Data Quality & Infrastructure: drive the “Product Data Quality” initiative for your domains. You will oversee the definition of metric frameworks, enforce rigorous instrumentation/taxonomy standards (Mixpanel), and ensure the delivery of trusted, documented dbt data models in Databricks.

• Experimentation Excellence:
  Uplevel the rigor and velocity of experimentation within your pods using Statsig. You will guide your team in designing complex experiments (e.g., triggering logic for CV assessments, Enso onboarding flows) and interpreting results to prevent “shipping to learn” without clear hypotheses.

• 0-to-1 Product Analytics (Hinge Select):
  Establish the foundational data architecture for Hinge Select. You will work with Engineering to solve complex data ingestion challenges (bridging internal Postgres, 3rd-party claims, and EHR data) to build the first comprehensive view of our hybrid care supply and demand.

• Cross-Functional Collaboration:
  
  Bridge the gap between technical data work and business outcomes. You will ensure your team’s work—whether it’s a predictive model for M2M referrals or a dashboard for weekly streak adoption—is actionable, accessible, and aligned with company OKRs.

We believe that remote work and in-person work have their own advantages and disadvantages, and we want to be able to leverage the best of both worlds. Employees in hybrid roles are required to be in the office 3 days per week, for the full 8 hours of a typical business day. The San Francisco office has a dog-friendly workplace program.

• Bachelor’s degree in Computer Science or related field, or equivalent professional experience

• 8+ years of experience in Data Science, Product Analytics, or a related technical field.

• 2+ years of people management experience (or 2+ years as a formal Tech Lead with mentorship responsibilities), with a track record of successfully hiring and developing talent.

• Strong proficiency in SQL and Python for data manipulation and analysis.

• Deep understanding of experimentation (A/B testing, causal inference) and statistical methods.

• Experience with modern data stacks: dbt, Databricks (or Snowflake/Big Query), Airflow, and BI tools like Mode, Tableau, or Looker.

• Ability to translate complex technical concepts into…