Job Location: Texas
Company:
AHI agilon health, inc.
Location:
Remote – TX
Job Title:
Principal Data Scientist
Job Description:
- At agilon health, we partner with physician groups to provide value-based care to senior patients. Our total care model is transforming healthcare by empowering PCPs to focus on the entire health of their patients, via quality of care, not volume of fees. We honor the independence of local physicians and serve as their long-term partners so they can be the doctors they trained to be.
- As a data scientist at agilon, you will tackle and solve some of the hardest problems in healthcare. Your modeling work will address use cases ranging from helping physicians make more accurate medical diagnoses to identifying patients who are at risk of not taking their medications.
- You will own the full end-to-end ML development lifecycle: engaging with stakeholders to scope out clinical and business opportunities, conceptualizing and training highly accurate predictive models, deploying models on our MLOps platform in AWS, and iterating and improving model accuracy over time.
- As a member of agilon’s Data Science team, you will join a community of enthusiastic data scientists dedicated to using ML to change health care. We have an agile team structure, a lively weekly seminar, and tremendous opportunity to grow with and within agilon.
- The models you train will be used directly in workflows that support agilon’s patients. Your work will make a difference in the lives of our patients and physicians.
Job Functions:
- Train predictive models to support a wide range of health care use cases, leveraging methodologies from statistics and machine learning.
- Build pipelines for model training and inference, using agilon’s MLOps stack in AWS.
- Write production-quality Python code.
- Work with large clinical datasets from agilon’s Data Lake, drawn from a diverse set of data sources.
- Collaborate with data scientists, cloud engineers, and clinical stakeholders from across agilon.
- Stay current with recent advances in machine learning and other technologies for value-based care.
Qualifications:
- Advanced degree (PhD, MS) in a quantitative field such as machine learning, statistics, economics, population health, epidemiology, computer science, or data science.
- Expertise in either machine learning/deep learning or classical statistics/causal inference.
- Proficiency in Python and SQL.
- Experience training and deploying models in a production environment.
- Experience collaborating with stakeholders on ML opportunities.
- Cloud experience preferred.
If you are excited about leveraging technology to have a meaningful impact on doctors and patients, have deep sense of ownership over your code, and track record of successful model development, we would love to hear from you.
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