Top Analytics Jobs in Minneapolis, MN

Leads enterprise data and analytics strategy, architecture, modernization, and delivery across cloud and on-premises environments. Oversees data platforms, engineering, integration, governance, quality, lineage, security, and compliance. Partners with executives to define roadmaps and investments, manages cross-functional teams and vendors, enables AI/ML capabilities, and mentors data professionals while driving scalable, trusted data solutions and measurable business outcomes.

Manages programmatic analytics and insights for client accounts, leading measurement frameworks, brand lift studies, incrementality testing, and A/B experiments. Develops media and campaign strategies, communicates performance insights to clients, and supports pitches and QBRs. Oversees, mentors, and develops analysts while partnering with Product, Engineering, Sales, and Customer Success teams to improve measurement tools, campaign optimization, and analytical capabilities.

Owns fraud performance analytics for depository products, including monitoring losses, approval rates, false positives, customer friction, and risk metrics. Builds data models, transformation pipelines, dashboards, scorecards, and monitoring frameworks. Conducts fraud deep dives and develops optimized rules, policies, thresholds, models, and decision strategies. Partners with Product, Engineering, Machine Learning, Data Engineering, Fraud Operations, and Risk teams to improve fraud detection and support product launches.

Leads analytics strategy and technical delivery for clients, specializing in Adobe Analytics and Customer Journey Analytics. Conducts measurement workshops, defines KPI and implementation strategies, oversees tagging and data quality, guides experimentation, and reviews dashboards and insights. Advises senior stakeholders, manages and mentors consultants, supports proposals and account growth, and contributes to Adobe Experience Platform initiatives involving Target, RT-CDP, and AJO.

Leads Toast’s analytics engineering function, owning enterprise data architecture, modeling strategy, analytics-layer development, and AI-ready semantic-layer vision. Builds and manages a team of analytics engineers, establishes roadmaps, partners with data engineering and business leaders, and drives scalable, governed data solutions across domains. Requires expertise in data modeling, dbt, SQL, stakeholder alignment, and people leadership.

Leverage data analytics, business intelligence, and Python to deliver strategic insights and tailored solutions for clients. Build reports, dashboards, data pipelines, and support data architecture and quality initiatives. Analyze data from multiple sources to identify trends, improve operations, and inform decision-making. Collaborate with stakeholders and team members while continuously developing technical skills and contributing to process improvements.

Leverage data analytics, business intelligence, and data science techniques to deliver strategic insights and solutions for clients. Build reports, dashboards, data pipelines, visualizations, and data architecture using tools such as Oracle BI, QlikView, Spotfire, and BIRT. Ensure data quality, manage stakeholder relationships, improve analytics processes, interpret complex datasets, and mentor junior team members while contributing to client projects and business strategy.

Lead programmatic analytics for clients and internal teams by analyzing campaign and model performance, designing tests, developing measurement solutions, recommending optimizations, and presenting actionable insights. Partner with Sales, Customer Success, Product, Engineering, and clients to align marketing strategies, reporting requirements, and optimization efforts with business goals.

Leads the strategy, architecture, implementation, and evolution of enterprise analytics platforms. Responsibilities include designing scalable data platforms, integrating digital and enterprise data, establishing governance and security standards, optimizing analytics and BI capabilities, evaluating cloud technologies, managing platform performance and risks, and mentoring technical teams. The role also requires close collaboration with executives, clients, Product, Engineering, Data Science, Marketing, and business stakeholders.

Lead and scale Runpod’s analytics and business intelligence function, managing analysts and BI practitioners while setting the analytics roadmap. Own core company metrics, consumption and marketplace analytics, self-service reporting, experimentation practices, and executive and board-level insights. Partner with Product, Finance, Engineering, Security, Supply, and Go-to-Market leaders to improve data quality, modeling, decision-making, and strategic outcomes.

Design and maintain analytical data models, transformation frameworks, data-quality checks, semantic definitions, and metric consistency across analytics and customer-facing products. Partner with engineering, product, and analytics teams to document data, improve lineage, and enable trustworthy self-service data usage. The role requires advanced SQL, analytics engineering, dimensional modeling, testing, and collaborative translation of business concepts into precise data definitions.

Leads analytics for Pricing and Supply, managing a team of approximately eight analysts. Partners with cross-functional leaders to prioritize analytical work, build dashboards and decision frameworks, improve metric quality, and generate insights into pricing, supplier coverage, marketplace performance, conversion, margin, and customer behavior. Coaches analysts, establishes scalable analytics processes, and collaborates with data engineering teams to improve data models, tooling, and self-service capabilities.

Partners with business leaders to transform complex data into actionable insights. Leads analytics initiatives involving data analysis, KPI frameworks, experimentation, forecasting, performance measurement, dashboards, and visualization. Uses SQL, Python, Power BI, and cloud data platforms to support strategic decisions, improve customer experiences, and drive business performance. Collaborates with technology, data engineering, and governance teams while mentoring analysts and promoting data-driven practices.

Analyze multi-channel fraud trends, develop data-driven insights and recommendations to prevent and detect fraud, evaluate controls and authentication strategies, support testing and implementation of fraud controls, and present executive-ready analytics to inform enterprise fraud strategy and prioritization.

Analyze complex datasets, build dashboards and reporting solutions, ensure data quality, automate processes, and present actionable insights to business leaders. The role partners with stakeholders across Operations to solve business challenges, improve performance, and support strategic decisions using SQL, DOMO, Alteryx, and related analytics technologies.

Analyze digital commerce data, develop reports and dashboards, identify trends and data-quality issues, and recommend process improvements. Collaborate with developers, business analysts, quality assurance teams, project managers, and business partners. The intern will apply data analysis, reporting, and visualization skills within an eCommerce environment.

Leads enterprise consumer insights and analytics to guide growth strategy, investment, innovation, portfolio decisions, category expansion, and M&A. Advises the CEO and executive leadership by integrating consumer behavior, marketplace, competitive, syndicated, transactional, and performance data. Builds predictive intelligence capabilities, monitors brand health, supports innovation and category entry, governs enterprise data ecosystems, and develops a high-performing consumer insights team.

Leads the organization’s business intelligence and analytics function, managing BI analysts and developers while overseeing reporting, dashboards, data governance, analytics delivery, and analytical data architecture. Partners with stakeholders to translate business needs into scalable data models, semantic layers, governed reporting, and actionable insights. Directs Power BI and Microsoft Fabric environments, advances data quality and self-service analytics, and evaluates AI-enabled tools. Responsibilities include team development, KPI standardization, predictive analytics, forecasting, and cross-functional solution delivery.

Build and maintain reliable data models, pipelines, metrics, dashboards, and self-service data products for Airbnb.org. Own data quality, testing, validation, incident response, and improvements to data assets. Partner with Marketing, Fundraising, Programs, Product, Data Science, and Engineering to translate business needs into trusted data solutions. Lead projects from ambiguous scoping through delivery, communicate technical tradeoffs, and mentor fellow data practitioners.

Lead end-to-end analytics for Netflix Ads demand, including media planning and campaign management tools, machine learning models, and agentic solutions. Partner with scientists, product managers, engineers, and data engineering to develop metrics, reliable analytics data, insights, and recommendations. Independently identify risks and opportunities, shape product roadmaps, and communicate findings to technical and non-technical stakeholders.

Provides customized healthcare operations analytics using Vizient and hospital data. Analyzes performance, costs, productivity, utilization, outcomes, supply use, and benchmarks; develops reports and actionable insights for hospital leaders. The role facilitates client meetings, translates findings into strategic and operational recommendations, ensures reporting accuracy, and contributes to mentoring and team best practices.

Own Hercules’ full data stack, including ETL from third-party providers into BigQuery, data modeling with dbt and medallion architecture, semantic-layer metric definition, and self-service business intelligence in Omni. Build reliable, maintainable systems and dashboards while applying strong software architecture, API design, code quality, and AI-assisted development practices.

Reviews, develops, validates, and refines dashboards, reports, visualizations, calculations, data sources, KPIs, and analytical workflows across BI platforms. The role documents findings, provides structured feedback, troubleshoots reporting accuracy, and evaluates AI-powered agents and workplace connectors used in analytics processes.

Own weekly and monthly sales performance reporting across SPINS, Circana, retailer portals, distributor feeds, and shelf data. Diagnose velocity, distribution, pricing, promotions, and competitive share; identify risks and opportunities; build buyer-facing category and sell-in decks; evaluate promotions and trade ROI; support Costco planning; and develop dashboards and scorecards that turn sales data into actionable insights.

Own end-to-end data products, including source onboarding, API and file-feed ingestion, orchestration, incremental and idempotent pipelines, Snowflake and dbt Cloud modeling, testing, documentation, alerting, and production reliability. Establish engineering standards, manage secrets and governance, use AI coding tools responsibly, collaborate with vendors and stakeholders, and mentor junior engineers.