Top Data Science Jobs in Minneapolis, MN

The Staff Data Scientist will advance machine learning models to optimize claim audits and improve business outcomes in healthcare.

The Staff Data Scientist will lead the development and deployment of ML and GenAI systems to detect billing errors and fraud in healthcare payments, collaborating with cross-functional teams.

The Data Scientist will develop tools for enhancing signature management capabilities, integrate diverse data holdings, and leverage AI/ML solutions for operational support.

Develop a tool to enhance signature management capabilities and integrate diverse data holdings, leveraging AI/ML solutions to meet operational needs.

Customer-facing data scientist advising customers on experiment design, statistical methodology, and experimentation architecture; running and analyzing A/B tests; building scalable experimentation programs; creating repeatable frameworks and technical enablement; partnering with Sales, Solutions Engineering, Product, and Engineering to drive customer success.

Build and productionize ML models and data infrastructure to analyze millions of chaos engineering experiments, detect and explain failures, recommend automated remediation, and integrate AI-driven failure analysis into Gremlin's product using techniques like causal inference, graph ML, time-series modeling, and reinforcement learning.

Lead and deliver end-to-end data science projects: design, build, deploy, and monitor ML/statistical models for credit risk, pricing, collections, and fraud. Partner with cross-functional teams to integrate models into production, set model development standards, mentor engineers, and maintain reliable ML pipelines and monitoring systems.

Lead development of orthomosaic tile imagery products for FireSat and SBEM: design and implement scalable mosaicking, orthorectification, and radiometric normalization algorithms; write production-ready code; author technical and customer-facing documentation; validate scientific quality; engage stakeholders and act as product owner for SBEM granule product; collaborate with engineers and scientists.

Lead radiometric calibration and image processing for multispectral infrared instruments, commission FireSat satellites, and develop/execute SBEM calibration plans. Implement production-ready pipelines, perform R&D to improve calibration, write production-quality code, and collaborate cross-functionally to maintain operational remote sensing data products and services.

The Data Scientist will build predictive models, drive forecasting, design experiments, and translate findings for stakeholders, optimizing healthcare operations.

Perform statistical analysis, predictive modeling, and data visualization on workforce and training data. Build dashboards, produce ad hoc analyses and decision-support products, advise on data governance/privacy, and collaborate with stakeholders to define metrics, deliverables, and reproducible analytic workflows.

Use statistical and causal inference methods to build, implement, and monitor marketing models (Bayesian MMM, multi-touch attribution), analyze A/B and uplift tests, partner with marketing to test and drive data-informed decisions from large web-product datasets.

Lead and grow a 4–6 person data science team, set the roadmap, deliver marketplace forecasting and production ML (matching, scoring), embed data science cross-functionally, and establish modeling, experimentation, and monitoring best practices.

Build and deploy machine learning models on large healthcare datasets, extract actionable insights, develop scalable data processing systems, collaborate with cross-functional teams, and communicate findings to stakeholders to improve patient outcomes.

Embedded on the central Data Science team, you will define the right problems, build metrics, run analyses and experiments, create reports, and drive data-informed recommendations end-to-end across growth, product, AI/automation, or partnerships.

Embed with a business unit to define problems, run analyses, design experiments, build reports, surface insights, and drive data-informed decisions across growth, product, AI, or partnerships.

Embedded in a core business area, own analytics end-to-end: define problems, build reports, run analyses, design experiments, surface insights, and drive data-informed decisions with stakeholders using SQL and Python.

Embed with a core business unit to define problems, design experiments, build reports, run analyses, surface insights, and drive data-informed decisions end-to-end across growth, product, AI/automation, or partnerships.

Embed with a business unit to define high-impact problems, pull and analyze data, build reports and experiments, surface insights, and drive recommendations end-to-end to improve product, growth, AI/automation, or partnerships.

Embed on a central Data Science team to define problems, build analyses, metrics and experiments, surface insights, and drive cross-functional decisions that move product, growth, AI/automation, or partnerships metrics end-to-end.

Design, validate, and operationalize predictive and machine learning models; mine and analyze large datasets; create visualizations and statistical validation; collaborate with teams to integrate solutions and communicate results to stakeholders.

The Principal Data Scientist will design and implement advanced AI/ML systems, lead development of large-scale machine learning solutions, and drive AI innovation in healthcare while mentoring other data scientists.

The Data Scientist II will design, build, and deploy machine learning models and data products, translating business problems into data-driven solutions, while collaborating with various stakeholders and ensuring reliable, production-ready outcomes.

Lead the technical development and automation of enrollment forecasting models, collaborating with various departments to enhance decision-making and forecast accuracy.

The Forward Deployed Marketing Data Scientist will work with AI customers and engineering teams to optimize AI-driven marketing campaigns through data analysis, diagnostics, and communication of insights to stakeholders.