Manager, Data Science, Forecasting & Routing

Back to jobsManager, Data Science, Forecasting & RoutingSan Francisco, CA (Hybrid)ApplyOur mission: eliminating every barrier to mental health. Spring Health is a global mental health company on a mission to eliminate every barrier to mental health. We're building a world where getting support is simple, personal, and built around the person, so care can continue through every job, move, health plan, and life stage.Our AI-native platform helps us deliver personalized support across self-guided tools, coaching, therapy, medication management, and specialty care. With outcomes independently validated by JAMA Network Open and the Validation Institute, Spring Health reaches more than 170 million people worldwide through leading employers, health plans, and partners.As an AI-native company, we believe technology should expand the reach, quality, and humanity of care. Every Spring Health team member is expected to use AI tools thoughtfully, apply human judgment to AI outputs, and keep building AI fluency in ways that support their role and our mission.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.  What you’ll do:  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 What success looks like: 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) What you’ll bring: 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...