Top Remote Analysis Reporting Jobs in Milwaukee, WI

Build and maintain Rayda’s data warehouse, analytics infrastructure, data models, transformation layers, pipelines, and workflows. Integrate product, billing, and customer interaction data from multiple platforms, improve data quality and governance, and create reliable datasets and analytical models. Enable self-service analytics and collaborate with Product, Growth, Commercial, and leadership teams to uncover usage patterns, churn risks, and expansion opportunities.

Supports data collection, cleaning, validation, reporting, dashboard preparation, and basic analysis. Tracks business and product metrics, identifies trends, documents datasets and processes, responds to ad hoc requests, and helps improve data usability while collaborating with cross-functional teams.

Build and maintain dbt data models, semantic layers, quality checks, and metric definitions. Own QuickSight architecture and administration, including datasets, refreshes, access controls, performance, AI features, and the Mode migration. Develop payor outcomes reporting, ensure data accuracy for analytics agents, and partner with data science, clinical, and business stakeholders on AI-native BI infrastructure.

Design, develop, and maintain Customer Data Platform solutions and data pipelines to create unified customer profiles, manage identity resolution, enable audience segmentation and activation, ensure data quality and governance, and support integrations with marketing, CRM, and cloud data systems.

Senior individual contributor responsible for Neo4j platform engineering: deploying and operating multi-node clusters, ensuring HA/DR, encryption, backup/recovery, troubleshooting performance, integrating observability (Prometheus/Grafana/New Relic/Splunk), managing Kubernetes deployments, and supporting graph data science tools (Bloom, GDS, Linkurious) for analytics consumers.

Design and manage financial systems for accurate cashback calculations, build and maintain reconciliation processes, ensure data integrity for yield-bearing instruments, collaborate with compliance, and partner with cross-functional teams to improve financial system efficiency.

Lead MyFitnessPal’s product analytics practice and team, advising the Chief Product Officer and senior leaders through actionable data insights. Define product metrics, oversee experimentation, analyze customer and marketing behavior, improve instrumentation and data infrastructure, and shape product strategy, roadmaps, engagement, and retention. This hands-on director role combines executive communication, team development, analytical leadership, and direct analysis across consumer iOS and Android applications.

Leads and develops an analytics engineering team that builds data pipelines, analytical models, reporting, and scalable data infrastructure. Partners with Product, Engineering, Growth, and Operations to deliver reliable, actionable data. Establishes governance, quality, testing, documentation, and modeling standards while prioritizing analytics projects and communicating with stakeholders.

The Actuarial Analyst will perform data analysis and modeling to support pricing, reserving, forecasting, and strategic decision-making, collaborating closely with multiple teams to deliver accurate insights and reports.

Manage and optimize mission-critical SQL Server databases hosted on AWS EC2 for a high-availability trading application. Responsibilities include performance tuning, database administration, HA/DR implementation, backup and recovery, security and compliance, monitoring, incident response, capacity planning, and 24/7 on-call support. Collaborate with developers, DevOps, and architects on database changes, production deployments, documentation, and disaster recovery testing.

Designs and optimizes ETL pipelines supporting analytics, data science, and machine learning. Builds labeling, retraining, MLOps, model monitoring, and production inference workflows. Contributes to lakehouse architecture, data modeling, governance, lineage, and quality. Uses infrastructure as code and containerization to create reproducible environments, collaborates with data scientists and BI teams, participates in code reviews, and improves engineering practices.