Senior Data Scientist, Forecasting and Routing Job at Spring Health (San Francisco)

Job Description

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.

Job Responsibility

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

Requirements

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

What we offer

Health, Dental, Vision benefits start on your first day
HSA and FSA plans are also available, with Spring contributing up to $1K for HSAs
Employer sponsored 401(k) match of up to 2%
A yearly allotment of no cost visits to the Spring Health network of therapists, coaches, and medication management providers for you and your dependents
Competitive paid time off policies including vacation, sick leave and company holidays
At 6 months tenure, parental leave of 18 weeks for birthing parents and 16 weeks for non-birthing parents
Access to Noom, a weight management program
Access to fertility care support through Carrot, in addition to $4,000 reimbursement for related fertility expenses
Access to Wellhub, which connects employees to the best options for fitness, mindfulness, nutrition, and sleep
Access to BrightHorizons, which provides sponsored child care, back-up care, and elder care
Up to $1,000 Professional Development Reimbursement a year
$200 per year donation matching to support your favorite causes

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