Staff Data Scientist – AI Personalization & Intelligence

Spring Health

San Francisco (CA)

Hybrid

USD 239,000 - 270,000

Full time

8 days ago
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Benefits offered by this job

Health, Dental, Vision benefits
401(k) match

Job summary

Spring Health in San Francisco is seeking a Staff Data Scientist to architect semantic and intelligence layers for profile data used by our AI-native platform. You will guide cross‑team design and shape how member, customer, and provider data flows support personalized decisioning.

You will leverage AI to validate patterns, create AI-augmented workflows, and establish guardrails for safe, compliant AI usage across large language models, with a focus on reliability and scalability.

Qualifications

  • 8+ years of experience building production ML/AI systems.
  • Experience with AI/ML architectures at scale.
  • Demonstrated ability to mentor engineers and lead cross‑functional teams.

Responsibilities

  • Take ownership of semantic and intelligence architecture across profile data domains.
  • Design AI-augmented workflows to multiply team output and enable real‑time inference serving on AWS.
  • Establish guardrails for safe and compliant AI usage across LLM-based systems.
  • Influence cross‑team projects and remove barriers to execution.
  • Mentor engineers and drive DS/ML best practices across the org.

Skills

ML/AI systems
Snowflake
OpenSearch
LLM orchestration
LangGraph
LangSmith
Staff leadership
Mentoring
Architectural design
Advanced degree

Education

MS/PhD in CS/ML

Tools

Snowflake
OpenSearch

Job description

Spring Health in San Francisco is seeking a Staff Data Scientist to architect semantic and intelligence layers for profile data used by our AI-native platform. You will guide cross‑team design and shape how member, customer, and provider data flows support personalized decisioning.

You will leverage AI to validate patterns, create AI-augmented workflows, and establish guardrails for safe, compliant AI usage across large language models, with a focus on reliability and scalability.

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