Top Analysis Reporting Jobs in St. Louis, MO

Lead Pager Health’s enterprise data and reporting strategy, build a centralized data and reporting shared services function, own internal dashboards and client-facing analytics, partner with Product and Engineering on data architecture and governance, mentor data teams, prioritize and deliver data initiatives, and drive continuous improvement in tooling, automation, and data storytelling to support growth, efficiency, and client outcomes.

Lead a team of data and infrastructure engineers to develop cloud-based data systems and solutions for analytics, ensuring best practices in data management and MLOps.

The Data Engineer will help build modern data infrastructure, designing ETL pipelines, modeling datasets, and collaborating with teams for improved data quality and accessibility.

The role involves managing Data Success Managers, overseeing data operations, supporting partners, and improving team workflows to deliver quality service.

The Data Scientist will build analytics infrastructure, conduct analysis and modeling, and collaborate with teams to enhance data impact and insights. Responsibilities include exploratory analysis, model building, and maintaining datasets for student success and operational efficiency.

As a Senior Analytics Engineer, you will design data models and pipelines, ensuring data integrity for reporting and analysis. Collaborate with cross-functional teams to enhance data architecture and support analytics goals using modern tools and practices.

The Senior Reporting & Analytics Consultant leads customer-focused reporting and analytics engagements, developing solutions, supporting implementations, and training clients, while ensuring project success.

As a Senior Data Engineer, you will design and maintain scalable data models, build production data pipelines, and support analytics across various business functions.

The Director, Product Analytics & Strategy will lead market expansion, define product strategy, analyze market opportunities, and drive cross-functional collaboration to shape product direction and company growth.

Lead design and implementation of shared, reusable analytics data models and pipelines. Drive standardization, governance, observability, and CI/CD for analytics; partner with Data Science, Infrastructure, and Product to certify metrics, modernize orchestration, and integrate AI-native tooling.