Data Scientist II

Medica • Minnetonka, MN

1d • Hybrid

About The Position

Medica is a nonprofit health plan with more than a million members, serving
communities in Minnesota, Nebraska, Wisconsin, Missouri, and beyond. We deliver
personalized health care experiences and partner closely with providers to
ensure members are genuinely cared for.

We’re a team that owns our work with accountability, makes data-driven
decisions, embraces continuous learning, and celebrates collaboration because
success is a team sport. It’s our mission to be there in the moments that matter
most for our members and employees. Join us in creating a community of connected
care, where coordinated, quality service is the norm and every member feels
valued.

As a Data Scientist II at Medica, you will lead initiatives in predictive
modeling to support population health strategies and enterprise decision-making.
You will partner with stakeholders across the organization to translate
analytical insights into scalable solutions and improved business processes.

Requirements

• Bachelor’s degree or equivalent experience in Data Science, Statistics, Computer Science, or a related field.
• 3+ years of professional experience beyond degree in advanced analytics, statistics, or data science.
• Experience applying predictive modeling or statistical analysis to real‑world business problems, preferably in a healthcare setting.
• Proficiency in at least one programming language commonly used for data science (e.g., Python, R, or SAS).
• Strong SQL skills and experience working with relational databases.

Nice To Haves

• Master’s degree in a quantitative discipline.
• Experience working with healthcare data, including claims, clinical, or operational datasets.
• Experience with advanced modeling approaches such as ensemble methods, deep learning, or natural language processing.
• Familiarity with source control and collaborative development workflows.
• Experience working in cloud‑based analytics environments and contributing to scalable data science pipelines.
• Ability to communicate complex analytical concepts clearly to non‑technical audiences.

Responsibilities

• Lead the development and maintenance of predictive models for medical expense and utilization forecasting to support population health strategies, financial planning, and enterprise decision‑making.
• Design and implement analytical solutions to identify potential fraud, waste, and abuse by detecting outliers, anomalous patterns, and emerging risk signals across claims and related data sources.
• Partner closely with the Special Investigations Unit (SIU) and other business stakeholders to investigate model findings, refine detection logic, and support case development through data‑driven insights.
• Apply natural language processing and large language model techniques to unstructured data, such as call center transcripts, to uncover trends, risks, and opportunities for improved member and operational outcomes.
• Research, evaluate, and apply appropriate statistical and machine learning modeling techniques such as regression, classification, anomaly detection, decision trees, and ensemble methods to improve model performance, interpretability, and business relevance.
• Collaborate with actuarial, finance, clinical, and enterprise analytics teams to embed predictive outputs into planning, monitoring, and decision‑making workflows.
• Contribute to the design and evolution of governed, scalable data science pipelines and model deployment processes in partnership with data engineering and IT teams.
• Support analytics infrastructure and tooling (e.g., Snowflake, Azure) to ensure models are reproducible, secure, and aligned with enterprise data governance standards.

Benefits

• competitive medical, dental, vision, PTO, Holidays, paid volunteer time off, 401K contributions, caregiver services and many other benefits to support our employees.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 501-1,000 employees