Top Analysis Reporting Jobs in Milwaukee, WI

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 Revenue Analytics Manager will analyze customer success and partner analytics, delivering insights to drive retention and revenue growth, working cross functionally with leadership and data teams.

The Senior Business Systems Analyst will leverage ServiceNow for automation, aligning solutions with business needs, enhancing user experience and driving AI-assisted solutions.

Lead and scale reporting and analytics in a fast-paced environment, managing a US and India-based team while delivering insights and resolving bottlenecks across data workflows.

The Senior Product Analyst will lead analytics for the Growth & LTV team, focusing on account and program performance, designing experiments, and ensuring data-driven product decisions.

The Cloud Data Architect will design scalable data architectures for SaaS solutions, set data standards, collaborate with engineering, and ensure data governance and optimization. Requires advanced SQL and cloud platform proficiency.

Seeking a Principal Solutions Specialist with deep expertise in RIA data management and client reporting, focusing on performance reporting workflows. The role includes collaborating with teams to enhance data capabilities and ensure accurate reporting across platforms.

As a Data Engineer II, you will build and optimize data pipelines in Databricks, ensure high-quality data delivery, and support generative AI applications. You will collaborate with data scientists and AI engineers to provide reliable data infrastructures and meet business needs.

As a Lead Product Data Analyst, you'll drive data-informed decision-making across teams, develop data products, collaborate on metrics, and influence product strategies.

Support sales intelligence by collecting, preparing, and analyzing sales and marketing data; maintain dashboards and data quality; run pipeline and win/loss analyses; translate findings into clear visualizations and reports for stakeholders.