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Spring Health is a global mental health platform on a mission to eliminate barriers to mental health care. The company operates an AI-native platform delivering personalized support through self-guided tools, coaching, therapy, medication management, and specialty care, reaching over 170 million people worldwide through employers, health plans, and partners.
As Staff Data Scientist for Personalization & Intelligence, you will architect the semantic and intelligence layers that make profile data (member, customer, provider) consumable for AI-native development and downstream product features. Reporting to the Senior Director of Engineering in Customer Value, you own a team's technical strategy and drive execution across critical systems.
Key responsibilities include: architecting semantic and intelligence systems with robust data contracts across platform teams; designing AI-augmented workflows (automated code generation, incident analysis) that multiply team output; establishing guardrails for safe, compliant LLM-based systems; influencing large cross-team projects and removing execution barriers; developing strategy from vision in ambiguous situations; building cross-functional relationships with business stakeholders; mentoring data scientists and engineers across the organization on DS/ML best practices; and participating in on-call rotations with focus on incident prevention.
Success means owning exemplary architectural components that set the standard for engineering excellence; designing AI workflows that transition the personalization decisioning layer from rules-based heuristics to predictive ML and deep learning; turning vision into clear strategy and objectives; driving best practices beyond your immediate team; empowering others through mentorship and context; handling escalations with calm leadership; and leading large-scale initiatives to reduce tech debt and improve architecture while meeting latency and scalability targets for production AI systems.
The role is hybrid based in San Francisco (44 Montgomery Street), requiring 2–3 days per week in office. Candidates must be based in the SF metro area or able to relocate within 90 days. Occasional travel for team on-sites is expected.
