Data Scientist II (ML Operations)

Medica • Minnetonka, MN

1d • Hybrid

About The Position

Medica is a nonprofit health plan with more than a million members that serves
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.

The Data Scientist II is a hands-on technical contributor responsible for
ensuring enterprise data science models and analytics workflows are reliable,
observable, and production ready. This role bridges data science development and
operational execution by supporting model deployment and monitoring,
troubleshooting modeling and coding issues across the ML lifecycle, and
improving the reproducibility and maintainability of analytical assets.

This position partners closely with Data Scientists, ML Engineers, and platform
teams to operationalize models, improve performance and reliability, and advance
reusable modeling and monitoring practices. The role also contributes to
documentation, process improvement, and scalable analytics engineering patterns
that benefit the broader Data Science organization.

Requirements

• Bachelor’s degree in Data Science, Machine Learning, Statistics, Computer Science, Software Engineering, or a related field
• 3+ years of experience in software engineering, data engineering, ML engineering, analytics engineering, data science, or analytics with exposure to production environments
• Strong proficiency in Python and SQL, with demonstrated ability to read, debug, and improve data science and ML code
• Experience supporting or deploying models into production and monitoring model performance over time
• Experience writing clear technical documentation and maintaining reproducible analytical workflows
• Ability to communicate technical concepts clearly and collaborate across teams

Nice To Haves

• Master’s degree in a related discipline
• Experience with ML monitoring, model governance, or regulated environments
• Familiarity with MLOps tooling, cloud platforms, and automated pipelines
• Experience working with healthcare data, including claims, clinical, or operational datasets

Responsibilities

• Implement and support model deployments; assist with CI/CD workflows, retraining processes, and production troubleshooting; ensure models meet operational readiness standards; maintain documentation and runbooks for repeatable operations.
• Design, implement, and maintain monitoring for model accuracy, drift, stability, data quality, and usage; analyze performance trends and proactively address degradation; support durable fixes for platform and pipeline issues.
• Contribute to governed, scalable data science pipelines and deployment patterns in partnership with data engineering and IT; improve reproducibility, security, and maintainability across Snowflake, Azure, and related tooling.
• Contribute new approaches, tools, or reusable assets that advance data science capabilities across the organization.

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