Top Data & Analytics Jobs in Minneapolis, MN

As an Analytics Supervisor, you will manage client analytics, providing insights and recommendations, mentor junior members, and ensure high-quality deliverables while utilizing Adobe Analytics.

Serve as a client-facing analytics partner for a major US retailer, delivering data-driven analyses and actionable insights using syndicated and retail data. Lead project scoping, multi-source integration, storytelling, and presentations while partnering cross-functionally to drive client outcomes.

The Research Intern will assist the research team in analyzing data, conducting literature reviews, and developing a research abstract for conference submission.

This role involves using data analytics to inform design strategies, creating visualizations, and collaborating with design teams for effective decision-making and client success.

The Director of Partner Integration manages data relationships with healthcare partners, leads a team of data engineers, and designs data pipelines for AI-driven workflows, focusing on client satisfaction and executive-level communication.

The Senior SAP Datasphere Engineer designs data pipelines, creates analytical models, optimizes data processes, and automates workflows in SAP environments while collaborating with business stakeholders and mentoring junior engineers.

The Data Engineer will develop and maintain data pipelines, ensuring data accessibility and quality while collaborating with various teams. Responsibilities include architecting data solutions on GCP, managing ETL processes, establishing data governance, and building CI/CD pipelines for automation.

The Data Scientist Intern will assist with data analysis, model development, and generate insights for improving healthcare outcomes within a SaaS environment under guidance.

The Sr. Business Systems Analyst will manage enterprise applications, lead initiatives for Oracle SCM, facilitate improvements, and support business needs with technical expertise.

The Data Engineer is responsible for developing data infrastructure, building data pipelines, managing data quality, and integrating analytics tools to support design and project operations.