Staff Data Scientist, Personalization & AI Intelligence

Spring Care, Inc.; San Francisco, Northern (CA, KY); Hybrid; USD 239,000 - 270,000; Full time

Benefits offered by this job

Health benefits

401(k) match

Wellness programs

Parental leave

Professional development reimbursement

Donation matching

Job summary

Spring Health in San Francisco is seeking a Staff Data Scientist to architect the semantic and intelligence layers enabling AI-native development and real-time personalization.

You will own data contracts across platform teams, design AI-augmented workflows on AWS, establish guardrails for safe AI usage, mentor engineers, and participate in on-call rotations to improve production reliability.

Qualifications

• 8+ years building production ML/AI systems and real-time data pipelines.
• Experience with AI-enabled workflows and data contracts across teams.
• Mentor engineers and drive architectural clarity in ambiguity.

Responsibilities

• Take ownership of semantic and intelligence architecture across profiles and contracts.
• Design AI-augmented workflows and real-time inference on AWS.
• Establish guardrails for safe, compliant AI usage and output quality.
• Influence large cross-team projects and remove blockers.
• Translate vision into objectives for core intelligence and recommendations.
• Build cross-functional relationships and balance stakeholder needs.
• Mentor data scientists and engineers across the org; lead DS/ML practices.
• Participate in on-call rotation to reduce incidents.

Skills

Production ML/AI systems

Inference microservices

Real-time data pipelines

Snowflake

OpenSearch

LLM orchestration

LangGraph

LangSmith

Mentoring

Architectural leadership

Education

MS/PhD in Computer Science or related field

Tools

Snowflake

OpenSearch

LangGraph

LangSmith

Job description

Spring Health in San Francisco is seeking a Staff Data Scientist to architect the semantic and intelligence layers enabling AI-native development and real-time personalization.

You will own data contracts across platform teams, design AI-augmented workflows on AWS, establish guardrails for safe AI usage, mentor engineers, and participate in on-call rotations to improve production reliability.