Top Analysis Reporting Jobs in Milwaukee, WI

Leads geospatial and GIS projects using the Esri platform to create maps, dashboards, spatial analyses, and field data solutions. Manages spatial data quality, project budgets, timelines, client relationships, proposals, and multidisciplinary deliverables. Advises clients on geospatial technologies and serves as a GIS project lead while supporting environmental assessments, infrastructure, permitting, and resource-planning projects.

Leads a data engineering team responsible for designing, developing, testing, deploying, and maintaining scalable data products and platforms. Sets technical direction, manages team performance and development, establishes engineering standards, and oversees data quality, security, governance, and operational excellence. Partners with product owners, enterprise architecture, information security, data governance, and business stakeholders to deliver data solutions. Defines team strategy and roadmap, evaluates emerging technologies, and communicates metrics and progress to senior leadership.

Supports data analytics and solution delivery through data profiling, modeling, visualization, testing, integration, and stakeholder collaboration. The intern participates in Agile ceremonies, helps transform business questions into data insights, explores approved AI capabilities, and contributes to projects using SQL, SSIS, Python, Snowflake, Microsoft Fabric, and ETL tools. This hybrid role requires full-time summer and part-time semester availability in a Milwaukee or Madison office.

Designs and develops data mastering and integration solutions using Markit EDM and Informatica. Responsibilities include gathering business and technical requirements, analyzing code, creating high- and low-level design documents, estimating schedules and effort, building and unit testing solutions, supporting configuration management, and working in an Agile environment.

Analyze IT business processes, gather and document requirements, interpret data, identify efficiency improvements, and recommend AI and automation opportunities. Assist with business cases, presentations, workflow documentation, and the design, testing, prototyping, and implementation of AI solutions using Microsoft Copilot Studio. Collaborate with business, technology, leadership, and project teams while gaining experience in process improvement, digital transformation, and emerging technologies.

Analyze supply chain and operations data, build dashboards and decision-support tools, support predictive and prescriptive analytics, gather data requirements, document methodologies, and complete an end-to-end summer project. The intern will work with SQL, Python, Excel, cloud data sources, decision intelligence platforms, and agile sprint practices while collaborating with planners, operators, managers, and business stakeholders.

Leads business analysis across multiple initiatives by gathering requirements, mapping processes, translating business needs into technical specifications, and identifying operational improvements. Partners with Finance, Risk, IT, Compliance, and project teams to deliver data-driven solutions. Monitors implementation outcomes, influences stakeholder priorities, supports regulatory alignment, and provides subject matter guidance to less experienced analysts.

The role involves design and development using Markit EDM, analyzing code, preparing design documents, and implementing data integration projects.

Leads the MPL data analytics team, defining strategy, prioritizing analytics intake, overseeing delivery, and ensuring data quality and governance. Hires, coaches, and develops analysts; manages capacity, standards, tooling, and operational initiatives. Partners with IT, data owners, product managers, and executives to deliver reporting, analytical solutions, automation, and insights supporting product P&Ls and business objectives.

Design, build, and maintain Power BI and Tableau dashboards; analyze large, complex datasets using SQL, Python, and statistical methods; partner with data engineering and business stakeholders to ensure data quality; translate findings into clear, actionable stories and executive-level presentations; support firmwide analytics growth and automation.