Top Analytics Jobs in Minneapolis, MN

Lead implementation and enablement of digital analytics tools across consumer applications. Translate technical specs, manage projects and cross-functional stakeholders, validate releases, oversee capacity planning, and drive process improvements for tag management and analytics deliveries.

Lead analytics owner for Financial Crimes Operations (FCO) DAR, delivering end-to-end data solutions and maintaining current reporting while enabling next-generation analytics, AI-driven automation, and compliance. Advise stakeholders, translate complex data into executive insights, manage projects/budgets/forecasts, mentor staff, and drive operational improvements across cross-functional teams.

The Senior Consultant is responsible for data analysis, reporting, and visualization while collaborating across teams to ensure data integrity, accuracy, and actionable insights.

Collect, process, and analyze complex datasets; build automated reporting, dashboards, and visualizations; perform statistical analyses; validate data quality; partner with stakeholders and engineering teams to deliver actionable insights and improve reporting processes.

Lead Finance Data & Analytics to build trusted data sources, governance, and analytics for Finance and cross-functional stakeholders. Manage analysts, drive data strategy and Snowflake data models, produce insights via SQL and Tableau, and deploy AI solutions to optimize finance decision-making and operations.

Design and build Toast’s enterprise analytics layer and AI-ready semantic layer in the data warehouse. Collaborate with domain teams and data engineering to implement hub-and-spoke architecture, define complex business logic in SQL, support scalability, partner with stakeholders, and provide technical mentorship.

Lead configuration management analytics by architecting solutions, automating data collection, and ensuring data integrity. Mine and model data from Oracle, Windchill, and TIPQA, apply statistical methods, build Power BI visualizations, and recommend process improvements using RCCA and Lean to improve workflow efficiency and stakeholder decision-making.

Lead design and implementation of shared, reusable analytics data models and pipelines. Drive standardization, governance, observability, and CI/CD for analytics; partner with Data Science, Infrastructure, and Product to certify metrics, modernize orchestration, and integrate AI-native tooling.

The Director, Research - Power Markets is responsible for leading the QA/QC process for long-term forecasting, advising leadership, and ensuring market insights are effectively integrated into forecasts.

The Manager of Data Analytics leads a team of analysts, managing analytics delivery, providing guidance, and enhancing processes for improved operational insights.

Lead design and build of ETL pipelines and Gold Layer tables in Databricks; develop semantic layers, data dictionaries, and AI-ready documentation; create dashboards and ad-hoc analyses to surface marketing and sales KPIs; partner with stakeholders to translate requirements into analytics-ready datasets and enable self-serve BI and agentic AI workflows.

Lead retail analytics to identify growth and efficiency opportunities, build strategic recommendations (store footprint, pricing, omnichannel), conduct market/competitive research, drive cross-functional initiatives, and deliver executive-ready analyses and frameworks to inform retail and digital strategy.

Lead building a data- and AI-enabled growth engine to improve pipeline quality and visibility. Define data governance, segmentation, scoring, and KPIs; operationalize demand-generation campaigns and tooling; prototype AI-driven automation and reporting; partner with vendors and sales/marketing to measure and improve pipeline conversion and ROI.

Ensure accuracy, integrity, and compliance of master and reference data across enterprise systems. Enforce governance, validate and remediate Salesforce and other system records, perform audits/cleansing/de-duplication, support migrations and integrations, produce reports and insights, and partner with global teams to improve data processes and adoption of standards.

This role drives data-driven decision-making in product analytics, collaborating with cross-functional teams to generate actionable insights and evaluate new launches to enhance platform growth.

Owner of the analytics foundation: design and maintain BigQuery/dbt models, pipelines, and Looker Studio reporting; build AI workflows and web apps on GCP; integrate marketing, e-commerce, and fulfillment data; ensure GCP ops, security, and reliability; use AI-assisted tools daily and collaborate with business and client stakeholders.

Lead end-to-end COGS and gross margin analysis for hardware and software products, model cost-saving scenarios, answer ambiguous executive questions, partner with data engineering/finance/product, build reliable datasets and analytical frameworks, and present recommendations to C-suite stakeholders.

Lead CX analytics strategy and operations by standardizing metrics, enabling self-service analytics, and embedding AI in the analytics lifecycle to enhance decision-making processes.

The Senior Analytics Engineer will design and implement scalable data solutions for Finance Analytics, reconcile data accuracy, and collaborate across teams to enhance financial datasets and reporting workflows.

Use advanced analytics and ML to design and monitor credit risk models, optimize underwriting and credit strategies, partner with Engineering/Product/Compliance, oversee portfolio performance and regulatory alignment, and lead cross-functional initiatives to balance growth, compliance, and risk mitigation.

Lead enterprise data strategy and MDM roadmap to establish trusted, governed master records across customer, product, pricing and supplier domains. Drive data governance, embed data quality into business processes, enable analytics/AI on high‑quality data, partner with business and IT, and lead a data and analytics team while managing budget and delivering measurable business impact.

The analyst will own planning for launches, build forecasting models, partner with stakeholders, and drive data-driven decisions using AI and analytics.

The Analyst I will own analytics workflows, drive improvements, build data models, and support business metrics while collaborating across teams.

The Data Product Analyst designs and manages data products for insurance domains, ensuring they meet analytical and compliance standards while collaborating with cross-functional teams.

The Analyst II will analyze data to optimize fraud strategies, develop machine learning models, and collaborate with teams to enhance product safety.