Job Overview

Come join our fast-growing group of deep-thinking engineers at ApolloMed! Our team of analysts, data engineers, data scientists, and researchers is looking for the right candidate to help grow our Risk Quality engine.

We are looking for an Intermediate Data Scientist who will support our Operations teams with insights gained from analyzing Fee-For-Service (FFS) and/or Medicare Advantage, Medicaid, and Commercial claims data. The ideal candidate is adept at using large data sets to design, implement, and report on relevant business and healthcare metrics. The candidate must have at least 2 years prior experience working with claims data. The candidate should have a deep understanding of concepts such as attribution, churn, and risk adjustment. Experience with implementing tools such as pricers, Hierarchical Conditional Categories, Clinical Classifications Software, Prevention Quality Indicators, etc. is a differentiator. The candidate must have strong experience implementing statistical measures in Python from a variety of sources (e.g., scientific and/or health literature, measure specifications, etc.). The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.

Responsibilities for Data Scientist

• Respond to requests from the Operations team in support of an internal Risk Quality engine.
• Mine and analyze data from company databases to design and communicate reliable metrics.
• Integrate appropriate methods and tools to extend engine offerings.

Qualifications for Data Scientist

• Strong problem-solving skills with an emphasis on product development
• Understanding of relevant concepts, such as attribution, churn, and risk adjustment
• 2 years experience wrangling claims data, and an awareness of common claims-based issues (e.g., claims lag, missing data, cross-walking, etc.)
• Strong Python programming skills
• Strong experience using relational database management systems to query and store data efficiently
• Experience using MongoDB is preferred
• Experience delivering metrics in a modern analytic environment (e.g., sharing Excel reports with executives, presenting Jupyter Notebooks, PowerBI, etc.)
• This position involves a heavy emphasis on developing proprietary measures related to core business outcomes