Senior Data Scientist, Forecasting and 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 Senior Manager of Data Science, the Senior Data Scientist I on the Routing & Forecasting team will lead the design and deployment of advanced forecasting and optimization models that power Spring Health’s precision care routing systems. You’ll define the analytical and technical direction for key initiatives that determine how we allocate care resources, predict demand, and ensure that members receive the right care at the right time. You’ll partner with Product, Engineering, and Clinical Operations to shape the roadmap for intelligent, data-driven care delivery.

Please note that this is a hybrid role based in San Francisco, with an expectation to be in office 2-3 days a week. Our office is located at 2 Embarcadero Ctr.

• →Lead the end-to-end design and delivery of high-impact data science projects — from problem framing and hypothesis generation through model development, validation, and deployment.
• →Develop, implement, and maintain advanced forecasting and routing algorithms, ensuring robustness, scalability, and reproducibility.
• →Define the technical direction for data science initiatives within the Forecasting & Routing domain, balancing long-term innovation with short-term impact.
• →Partner with stakeholders across the business to translate ambiguous operational needs into clear research questions and data products that drive measurable results.
• →Apply advanced statistical and ML techniques to complex forecasting and routing challenges.
• →Champion MLOps best practices, including automated model monitoring, versioning, logging, and alerting in production environments.
• →Collaborate closely with engineering to ensure models are deployed efficiently using tools like AWS SageMaker, dbt, and GitHub, with strong observability and CI/CD standards.
• →Mentor junior data scientists, contribute to peer reviews, and help shape team standards for code quality, experimentation, and documentation.
• →Communicate insights clearly to technical and non-technical audiences, influencing product and operational decisions through data-driven recommendations.

• Ownership and successful delivery of multiple, complex data science projects with measurable business impact.
• Forecasting and routing models consistently meeting or exceeding accuracy and reliability benchmarks.
• Demonstrated leadership in defining best practices in experimentation, MLOps, and model governance.
• Strong cross-functional relationships with Product, Engineering, and Operations that result in faster decision-making and higher confidence in model outputs.
• Clear evidence of mentorship and technical influence within the data science team.
• Contributions to roadmap and strategy that improve scalability, efficiency, and care outcomes across Spring Health’s precision care systems.

• 4–6 years of professional experience in data science, machine learning, or a related quantitative field.
• Deep proficiency in Python and SQL, with proven ability to design and maintain production-grade codebases.
• Demonstrated expertise in time series forecasting, predictive modeling, and causal inference.
• Hands-on experience building and deploying ML models using AWS SageMaker, with strong understanding of MLOps, model monitoring, and lifecycle management.
• Familiarity with Snowflake, dbt, GitHub,scikit-learn, and MLflow.
• Strong understanding of experimental design, statistical inference, and uncertainty quantification.
• Ability to navigate ambiguous or incomplete data, formulate hypotheses, and deliver elegant, data-driven solutions.
• Excellent communication skills and ability to synthesize complex analyses into actionable recommendations for leadership.
• Demonstrated ownership of projects that delivered measurable operational or business impact.
• Passion for applying data science to real-world problems in mental healthcare.

The target base salary range for this position is $183,500 - $205,550 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.