Sr. AI Insights Engineer

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Position Summary: 

As an AI Insights Engineer at agilon health, you will support AI products within agilon’s Tech Group by analyzing their real-world performance and communicating results to stakeholders. The AI Team develops prioritization models, unstructured data pipelines, clinical suspect identification, and clinical risk models. In this role, you will study how these models function in our population, and you will develop the analyses and dashboards needed to monitor their success in the organization. You will work closely with stakeholders across the organization to understand the clinical, business, and technical requirements, and be responsible for the communicating the impact that AI products provide at agilon.  

Essential Job Functions: 

• Build dashboards and analyses to monitor AI product impact and communicate the insights across the organization. 

• Create analytical data models and pipelines to support AI products. 

• Support development of machine learning and deep learning models by analyzing and preparing structured and unstructured healthcare data.  

• Collaborate with Insights Engineering, Clinical Analytics, and Centralized Operations teams to drive real-world outcomes.  

• Contribute to the development of our AI products in a fast-paced, agile environment. 

Required Qualifications:  

Minimum Experience 

• 5+ Years of experience in a related field, including Analytics, Data Science, or Data Engineering.  

Education/Licensure 

• Bachelor’s and/or master’s in a quantitative field, such as Computer Science, Data Science, or Mathematics. 

Knowledge, Skills, and Abilities: 

• Strong SQL skills and experience (prefer Snowflake + dbt) with data visualization tools (prefer Sigma).   

• Excellent communication skills and the ability to explain complex concepts to non-technical stakeholders.  

• Proficiency in Python programming and familiarity with ML libraries and practices (e.g., scikit-learn, pandas).  

• Good knowledge of statistical analysis and predictive modeling techniques.  

• Intellectual curiosity and a passion for using data to solve real-world problems.  

• Enthusiasm for learning and adapting in a dynamic startup environment. 

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Pay Range: ​

Salary range shown is a guideline. Individual compensation packages can vary based on factors unique to each candidate, such as skill set, experience, and qualifications.