Top Senior Analytics Jobs in Minneapolis, MN

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.

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.

Lead transformation of frontline monitoring from rule-based to AI-driven analytics. Own end-to-end model lifecycle, champion AI/LLM tools, deliver risk-detection solutions, advise senior leaders, and build an AI-fluent analytics team while ensuring governance and audit defensibility.

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

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.

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

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.

Designs, builds, and operates ELT data pipelines and analytical datasets for Platform Analytics. Curates and models source data into conformed datasets, ensures performance, reliability, and cost efficiency, contributes to target-state architecture, mentors junior engineers, and uses AI coding tools to accelerate development and delivery.

Design, build, and maintain scalable dimensional data models, semantic layer, and production transformation pipelines. Collaborate with Data Engineering, Data Science, BI, DevOps, and Product to enable AI-ready data, ensure data quality and governance, support ML feature delivery, and coach analytics team members for robust, production-ready data products.

Lead technical design and architecture for analytics engineering: build and govern the semantic/metrics layer, optimize dbt and Snowflake for performance and AI use cases, mentor engineers, partner with Data Science and Engineering, drive data quality, CI/CD, observability, and deployment of third-party data and emerging tooling to support analytics, ML, and agent-based products.

The Senior Data Engineer will design and implement scalable data models in BigQuery using dbt for analytics and reporting, ensuring data governance and optimal performance.

Lead and grow a team of analytics engineers while remaining hands-on with SQL, dbt, and Snowflake. Own roadmap and semantic layer development, build trusted, governed data products, partner with cross-functional stakeholders, champion data quality and observability, and hire and coach engineering talent to deliver scalable analytics and AI-ready foundations.

Lead a team of analysts and data scientists embedded in sales to build rigorous pilot analyses, create executive-ready business cases, expand consultative analytics across the partner lifecycle, and publish industry insights while coaching and scaling the Solutions Analytics function.

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.

The Senior Analytics Engineer will develop data pipelines, build models, and create dashboards to provide actionable insights for various teams. The role requires collaboration with multiple stakeholders to meet analytical needs and ensure data governance.

The Senior Reporting & Analytics Consultant leads customer-focused reporting and analytics engagements, developing solutions, supporting implementations, and training clients, while ensuring project success.

The Staff Analytics Engineer will own the Financial Subledger Data Platform, build dbt models, implement data quality controls, and mentor a junior engineer, ensuring high operational reliability and cross-functional collaboration.

Lead and execute reporting, analytics, BI, and AI strategy for Sales, Credit, and Servicing. Build and coach a high-performing analytics team, act as product owner for analytics capabilities, drive platform adoption (Tableau, Snowflake, Databricks, Salesforce/nCino), establish governance and KPI frameworks, and influence executive stakeholders to deliver data-driven business outcomes.

The Senior Analyst executes customer decisioning strategies, monitors performance reporting, collaborates with strategy owners on KPIs, and conducts data analysis while adhering to governance standards.

Lead client analytics engagements end-to-end, manage delivery timelines and economics, mentor data teams, design KPIs and business cases, translate complex data into actionable insights, implement cloud data platforms, BI, ETL and scripting solutions, and run workshops and knowledge transfer for non-technical stakeholders.

Lead the insights & analytics team to manage databases, standardize reporting, and deliver syndicated (Circana) insights and KPI dashboards to inform strategic planning, budgeting, and investment decisions across categories, channels, and customers.

Lead decision science efforts for corporate and people analytics by designing experiments, performing explanatory and inferential analyses, building diagnostic and multivariate models, synthesizing insights, influencing strategic decisions, ensuring data quality and best practices, and mentoring analytic talent while partnering across the enterprise.