Top Remote Analysis Reporting Jobs in Milwaukee, WI

Lead the data organization to define data strategy, build scalable cloud-native pipelines, enable self-service analytics, drive AI/ML initiatives, and manage a multidisciplinary team to inform product, clinical, and business decisions.

As a Data Engineer at LiveKit, you will manage the analytics infrastructure, develop scalable GCP-based data pipelines, and ensure effective data movement and transformation processes, while collaborating with the Analytics and engineering teams.

Lead statistical programming for clinical trials, oversee programming deliverables, ensure compliance with CDISC standards, supervise staff, and develop programming solutions.

The Sr Data Enablement Specialist will enhance data governance, support BI tools, implement AI workflows, and provide training resources to improve data utilization across teams.

Partner with customers and sales to design and present scalable Databricks Lakehouse architectures, build reference architectures and demos, consult on big data, ETL, and ML projects, validate integrations, and drive technical wins and adoption across accounts.

The Data Engineer Senior will optimize data pipelines, work within scrum teams, mentor others, and improve data quality, reliability, and governance.

The role involves supporting sales and services initiatives through data analysis, relationship management, and cross-functional collaboration to inform strategies and optimize processes.

The Program Integrity Data Scientist II develops and deploys analyses for payment accuracy and fraud detection, collaborates with teams, and analyzes claims data for anomalies.

As a Senior Data Engineer, you will build and maintain the data platform infrastructure, oversee data lakehouse architecture, and collaborate with product engineering to ensure reliable data delivery and adherence to data contracts.

The Data Quality Analyst will manage customer data migrations, ensuring accuracy and success while working with internal teams to facilitate the process. They will spend 60% of their time with clients and 40% on technical tasks like writing SQL queries and analyzing data structures.