Medica is looking to solve the problem of delivering personalized health care experiences and partnering closely with providers to ensure members are genuinely cared for, by leveraging data science and predictive modeling to support population health strategies and enterprise-level decision-making.
Requirements
- statistical modeling and data engineering
- Advanced modeling techniques (e.g., ensemble methods, deep learning)
- Expertise in SQL, Python, R, SAS
- Familiarity with code source control (Git, GitLab, GitHub)
- Experience with cloud platforms and data science IDEs (e.g., Jupyter Lab, Anaconda, Spyder)
- Strong data engineering and pipeline development skills
Responsibilities
- Design and implement machine learning models for real-time forecasting of healthcare utilization and cost trends
- Research and apply prescriptive solutions using data science and statistical methods to enhance modeling outcomes
- Develop and validate predictive models using ensemble methods and deep learning techniques
- Collaborate with internal stakeholders to develop data governance strategies and build robust data science pipelines
- Collaborate with actuarial, finance, and enterprise analytics teams to embed predictive outputs into planning and decision-making processes
- Support infrastructure design in collaboration with IT (e.g., Snowflake, Azure) to ensure scalable, secure, and governed model deployment
Other
- Bachelor's degree or equivalent experience in related field
- 3+ years of work experience beyond degree in advanced analytics, statistics, or data science, preferably within healthcare
- Masters in a quantitative discipline (preferred)
- Office role, which requires an employee to work onsite at our Minnetonka, MN office, on average, 3 days per week
- Demonstrated experience in healthcare-related projects (preferred)
