Lead AI Insights Engineer

Job Responsibilities:

• Leverage LLM tools to drive early disease identification and clinical recommendations through unstructured clinical data including notes and images.
• Create production-grade AI products including supporting data pipelines, monitoring, and performance analysis.
• Communicate the value and opportunities of AI to internal stakeholders.

Qualifications:

• Minimum 7+ years in Analytics, Data Science, or Data Engineering, with 3+ years in healthcare, preferably value-based care.
• Bachelor’s or master’s in a quantitative field such as Computer Science, Data Science, or Mathematics.
• Strong SQL skills with Snowflake and dbt, advanced programming in Python, and experience with cloud AI tools like Snowflake Cortex and AWS Sagemaker.

Ideal Candidate:

• Deep knowledge of healthcare data sources and analytical methods including FHIR, claims, pharmacy, and lab data.
• Understanding of value-based care concepts in the US, including Medicare payment models and quality of care.
• Excellent communication skills to explain complex concepts to non-technical stakeholders, with enthusiasm for learning and adapting.

Work Environment:

• Remote position based in the USA.
• Collaborative agile environment working with Market Operations, Insights Engineering, and Clinical teams.
• Commitment to diversity and equal opportunity, with a focus on protecting candidate privacy and security.