# Staff Data Scientist, Personalization & Intelligence at Spring Health

- Company: Spring Health
- What the company does: Eliminating barriers to mental healthcare. Clinically-proven technology with world-class providers to deliver precisely what your employees need.
- Company website: https://www.springhealth.com
- Type: Startups
- Level: Senior
- Location: San Francisco, CA (Hybrid)
- Work setup: Hybrid
- Pay: $239K to $270K base salary per year (USD)
- Posted: 2026-09-03
- Apply by: 2026-10-18
- Apply: https://job-boards.greenhouse.io/springhealth66/jobs/4730514005
- Page: https://www.1752.vc/careers/jobs/spring-health-staff-data-scientist-personalization-and-intelligence/

## About the role

The target base salary range for this position is $239,000 - $270,000, 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.

## What they're looking for

- Take ownership of a team’s semantic and intelligence architecture—providing system-wide design guidance for profile data (member, customer, provider) and ensuring robust data contracts across platform teams
- Establish guardrails for safe and responsible AI usage across your team, covering security, compliance, and output correctness, specifically for LLM-based systems, ensuring compliance and correctness
- Critically influence large, cross-team projects—ensuring execution without delay or compromise, and anticipating and removing barriers of all kinds
- Develop strong working relationships cross-functionally and with business stakeholders, make sound tradeoffs between competing needs across short- and long-term horizons
- Empower data scientists and engineers to set ambitious goals and turn vision into reality, mentor and develop engineers across the organization, not just your immediate team, mentoring on DS/ML best practices
- Participate in an on-call rotation, push for better preparation and planning to reduce the frequency and impact of production incidents

Tags: Technology