Manager, Data Science, Forecasting & Routing

At Spring Health, we’re on a mission to revolutionize mental healthcare by removing every barrier that prevents people from getting the help they need, when they need it. Our clinically validated technology, Precision Mental Healthcare, empowers us to deliver the right care at the right time—whether it’s therapy, coaching, medication, or beyond—tailored to each individual’s needs.

We proudly partner with over 450 companies, from startups to multinational Fortune 500 corporations, as a leading provider of mental health service, providing care for 10 million people. Our clients include brands you use and know like Microsoft, Target, and Delta Airlines, all of whom trust us to deliver best-in-class outcomes for their employees globally. With our innovative platform, we’ve been able to generate a net positive ROI for employers and we are the only company in our category to earn external validation of net savings for customers.

We have raised capital from prominent investors including Generation Investment, Kinnevik, Tiger Global, Northzone, RRE Ventures, and many more. Thanks to their partnership and our latest Series E Funding, our current valuation has reached $3.3 billion. We’re just getting started—join us on our journey to make mental healthcare accessible to everyone, everywhere.

Reporting to the Director of Data Science and partnering closely with Product, Engineering, and Actuarial teams, the Manager of Data Science will lead a team responsible for forecasting care utilization and optimizing member routing decisions. This role will drive the development of decision systems that balance clinical outcomes with business economics, enabling sustainable growth of Spring Health’s care models.

Please note that this is a hybrid role based in San Francisco, with an expectation to be in the office 2–3 days per week at our 44 Montgomery Street location. Candidates must be based in the San Francisco metro area or able to relocate independently within 90 days of their start date. Occasional travel will be required for team on-sites. 

• →Lead and develop a team of data scientists working on utilization forecasting and care routing optimization
• →Define and execute the data science roadmap supporting forecasting accuracy, experimentation, and decision systems
• →Build and productionize forecasting models that predict care utilization across customer lifecycle stages
• →Develop and iterate on routing algorithms and experimentation frameworks to influence member care pathways
• →Partner with Product and Engineering to translate models into scalable, real-time systems
• →Collaborate with Actuarial and Finance teams to align forecasts with pricing assumptions and business targets
• →Design and analyze experiments to evaluate interventions that shift member behavior and care utilization
• →Establish monitoring systems to detect deviations in utilization trends and trigger interventions
• →Communicate insights, risks, and trade-offs clearly to senior stakeholders
• →Ensure high standards for model quality, documentation, and reproducibility

• Forecast accuracy for care utilization within defined error thresholds across new and existing customers
• Measurable improvement in gross margin driven by data science initiatives
• Reduction in variance between expected and actual utilization levels
• Experimentation velocity (e.g., number of experiments launched and evaluated per quarter)
• Adoption rate of data-driven routing strategies in production systems
• Stakeholder satisfaction with data science outputs and decision support
• Team delivery reliability (projects completed on time and within scope)

• 5+ years of experience in data science, with at least 2+ years managing teams
• Experience building and deploying machine learning models in production environments
• Strong foundation in statistical modeling, experimentation, and causal inference
• Experience working cross-functionally with product and engineering teams to ship data products
• Proven ability to translate ambiguous business problems into structured analytical solutions
• Strong communication skills, with the ability to influence non-technical stakeholders
• Experience managing projects with multiple stakeholders and competing priorities
• Experience in healthcare, benefits, or risk-based business models
• Experience with forecasting, time series modeling, or demand planning
• Familiarity with experimentation platforms and behavioral interventions
• Experience working on marketplace, routing, or recommendation systems
• Experience with cost optimization or unit economics problems

The target base salary range for this position is $183,000 - $205,500, and is part of a competitive total rewards package including equity and benefits. Individual pay may vary from the target range and is determined by a number of factors including experience, location, internal pay equity, and other relevant business considerations. We review all employee pay and compensation programs annually using Radford Global Compensation Database at minimum to ensure competitive and fair pay.