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Principal Data Scientist

Job in Eagan, Dakota County, Minnesota, USA
Listing for: Blue Cross & Blue Shield of Minnesota
Full Time position
Listed on 2025-12-27
Job specializations:
  • IT/Tech
    AI Engineer, Machine Learning/ ML Engineer, Data Scientist, Data Analyst
Salary/Wage Range or Industry Benchmark: 100000 - 170000 USD Yearly USD 100000.00 170000.00 YEAR
Job Description & How to Apply Below

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 MN is hiring a Principal Data Scientist in Eagan, MN. The Principal Data Scientist will lead the design and deployment of advanced AI solutions, leveraging Large Language Models (LLMs) and innovative agentic AI architectures. This individual will develop scalable systems where multiple AI models collaborate to produce insights and enhance efficiency across the organization.

In this role, you will drive the development of cutting‑edge AI models and scalable systems that enable collaboration across multiple models to deliver actionable insights. You will design and implement solutions that ensure accuracy, reliability, and performance while incorporating best practices for fairness and transparency. Working closely with cross‑functional teams, you will assess potential risks, optimize workflows, and establish governance processes for model monitoring and lifecycle management.

Additionally, you will stay current with emerging technologies and regulatory requirements, mentor data scientists and engineers, and champion innovative approaches to integrating LLMs and agentic AI architectures into enterprise applications.

The ideal candidate brings at least seven years of experience in data science, progressing from predictive analytics and machine learning to sophisticated LLM‑driven AI applications. You excel at designing solutions that synthesize data, streamline operations, and deliver impactful insights. Success in this role requires strong partnership skills to translate complex business problems into effective data science and machine learning solutions, while maintaining a balance between innovative advancements and responsible governance for safe, scalable AI deployment.

Your

Responsibilities
  • Lead 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.
  • Act as a mentor to junior data scientists around mature data science practices e.g., readable code, thorough documentation, comprehensive experimentation.
  • Work with autonomy 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.
  • Work hand‑in‑hand 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.
Required Skills and Experience
  • 7+ 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).
  • Advanced 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.
  • Strong communication skills and ability to deliver highly technical results to…
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