Senior Data Scientist

Blue Cross Blue Shield of Minnesota•Eagan, MN

10d•Hybrid

About The Position

About Blue Cross and Blue Shield of Minnesota At Blue Cross and Blue Shield of Minnesota, we are committed to paving the way for everyone to achieve their healthiest life. We are looking for dedicated and motivated individuals who share our vision of transforming healthcare. As a Blue Cross associate, you are joining a culture that is built on values of succeeding together, finding a better way, and doing the right thing. If you are ready to make a difference, join us. The Impact You Will Have Blue Cross and Blue Shield of Minnesota is looking for a Senior Data Scientist on our Methods Analytics team! The Senior Data Scientist on the Identification & Stratification Method Analytics team leads the design, development, and continuous improvement of data-driven processes that identify and prioritize members for care management and utilization management programs. This role focuses on applying statistical and population health methodologies—rather than heavy technical engineering—to analyze member populations, uncover insights, and guide program targeting strategies. This position is responsible for building and maintaining production identification and stratification workflows that run on a recurring cadence (daily, weekly, monthly) to support both internal care management teams and external vendor programs. The Senior Data Scientist collaborates closely with clinical, product, and analytics partners to refine existing methodologies, develop new identification approaches, and ensure alignment with evolving business and care delivery goals. The ideal candidate brings a strong healthcare background—such as population health or epidemiology—with deep expertise in statistical analysis, experience working with care management or utilization management concepts, and a collaborative, problem-solving mindset.

Requirements

5+ years of related professional experience. All relevant experience including work, education, transferable skills, and military experience will be considered.
Hands-on experience in analytics and data science (specific areas of interest include classification/regression, unsupervised learning, time-series/sequence models, NLP, explainability methods, deep learning).
Solid demonstrable proficiency in data science tools such as Python, R, Spark, SQL.
Experience implementing predictive algorithms and associated statistical analysis/inference in a data science/ML workflow manipulating both structured and unstructured data.
Experience crafting and communicating highly technical results to a diverse audience.
Comfortable working as part of a team and taking the lead.
High school diploma (or equivalency) and legal authorization to work in the U.S.

Nice To Haves

Bachelor's degree.
Experience with health care data
Experience with AWS tools
Experience with version control (for example Git Version Control system)
Proficiency with Data Bricks or similar tools

Responsibilities

Take lead on data science projects to design and implement models and experiments from end to end, including data ingestion and preparation, feature engineering, analysis and modeling, model deployment, performance tracking and documentation.
Lead-by-example junior data scientists around mature data science practices e.g., readable code, thorough documentation, comprehensive experimentation.
Work with business partners to convert ambiguous business problems in clear data science/ML specifications.
Use contextual business acumen to convert model predictions/results into impactful insights and provide actionable guidance on risks and limitations.
Drive conversations with product managers, data engineers, and subject matter experts to ship new models, algorithms and improvements continuously and collaboratively into production.
Use combination of machine learning knowledge and contextual business acumen to convert results into impactful insights and provide actionable guidance on risks and limitations of model.
Write narrative documents for model specification and performance analysis to communicate findings and recommendations to teammates, stakeholders and executive leadership.