Top Analysis Reporting Jobs in Milwaukee, WI

Analyzes servicing, collections, application funnel, and contact-center data to identify performance gaps and inform business decisions. Builds automated reports, partner data files, Snowflake and dbt models, and operations dashboards. Maintains metric definitions, audits models, reconciles partner data, and develops business-case analyses. Uses AI tools to improve analytics workflows and collaborates with data engineering, product, and business teams.

Build and maintain production data pipelines and foundational datasets for Market Intelligence. Automate survey ingestion, cleaning, joining, scheduling, monitoring, and reporting-layer integration. Develop repeatable queries, improve data quality practices, document assumptions, support reproducible outputs, and translate research needs into technical solutions. The role requires close collaboration with technical and nontechnical stakeholders and ownership of reliable data infrastructure.

Own commercial and growth analytics for GeneDx’s top line, answering questions about volume, revenue, pricing, coverage, field capacity, and product performance. Serve as a senior advisor to commercial and product leaders, structure ambiguous problems, lead analyses end to end using AI agents, communicate executive-ready insights, support evidence-based decisions, monitor outcomes, and surface emerging opportunities. Maintain analytical governance, apply measurement and experimental design, and contribute reusable methods to the analytics function.

Leads operational analytics for the Take 5 Oil Change network, translating transactional and market data into insights that improve sales, profits, volume, and shop performance. Responsibilities include complex analysis, KPI reporting, dashboards, executive presentations, operational initiative measurement, stakeholder collaboration, data-quality improvement, and mentoring analysts. The role requires strong Excel, SQL, financial modeling, communication, and multi-shop operations experience.

Supports medical education evaluation and grant-seeking through data manipulation, statistical analysis, reporting, visualization, and stakeholder communication. The role prepares reports, presentations, conference abstracts, and publications using Excel, R, SPSS, SAS, and related tools. It also explores open-ended evaluation questions, manages multiple projects, and applies generative AI to accelerate report drafting, data validation, formatting, and deliverable quality assurance.

Lead marketing analytics: own reporting frameworks, dashboards, and data quality; monitor KPIs; run A/B tests and experiments; build attribution, forecasting, segmentation, and budget-allocation models; automate workflows and drive continuous measurement improvements.

Leads enterprise Business Intelligence strategy, architecture, governance, security, and self-service analytics adoption. Architects solutions across Power BI, Tableau, SAP BusinessObjects, and Databricks; establishes semantic models, data standards, DevOps, CI/CD, and reporting performance practices. Partners with executives and technical teams to modernize analytics platforms, reduce manual reporting, and enable AI-ready decision-making. Mentors BI professionals and drives enterprise data literacy and analytics transformation.

Analyze market and live data to set dynamic ticket prices using Uptick, build strategic pricing recommendations, communicate with clients about strategy and performance, and collaborate with BI and engineering to improve product performance.

Analyze healthcare operations data to identify bottlenecks, model advocate capacity and supply-demand, build scalable Hex dashboards, refine SQL and dbt data transformations, and translate complex findings into operational recommendations. The role partners with Operations, Engineering, Product, Marketing, and Finance to improve workflows, reporting, resource allocation, and business outcomes across the patient and advocate journey.

Leads LTK’s Data Engineering team, owning technical direction, architecture, pipelines, data products, governance, quality, reliability, and platform modernization. Manages and develops engineers, drives roadmaps and complex initiatives, partners with cross-functional stakeholders, and balances scalability, security, performance, cost, and business priorities. Establishes engineering standards, improves operational practices, manages risks and dependencies, and builds trusted, reusable data capabilities supporting analytics, reporting, products, and AI use cases.