Top Senior Analysis Reporting Jobs in St. Louis, MO

As a Senior Actuary, you'll lead profitability assessments, refine pricing, develop actuarial models, mentor juniors, and oversee regulatory filings.

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 Senior Data Analyst transforms data into insights to guide business decisions, conducts analyses, and improves data collection systems.

The Data and Reporting Architect will lead the design of data architectures and reporting systems, addressing complex data challenges and ensuring compliance with regulatory standards. Responsibilities include mentoring engineers, defining data quality frameworks, and collaborating with various teams to implement scalable solutions.

The Senior Product Analyst will lead product analytics, design A/B tests, build dashboards, and integrate customer insights to drive product strategy and improve customer experience.

Oversees analytics reporting and provides critical analysis to support strategic decisions across various business functions. Leads teams, develops reporting solutions, monitors metrics, and manages business processes.

Responsible for designing and operationalizing quality analytics for improving Medicare Advantage Stars and HEDIS outcomes. This role involves building analytic assets, translating data into insights, and ensuring quality reporting.

Lead complex data migration efforts for customers. Oversee the migration lifecycle, ensure data accuracy, and mentor junior team members.

The Senior BI Analytics Engineer will design and deliver data models for analytics, ensuring data quality, and collaborating across teams to enhance AI-driven reporting and querying capabilities.

Lead design, build, and maintain scalable data pipelines and infrastructure using Azure Databricks, ADF, and SQL Server. Develop OLTP and dimensional models, integrate Salesforce and SaaS sources, implement batch and real-time processing, enforce data governance and CI/CD, troubleshoot performance, mentor team members, and drive improvements to reduce technical debt and improve cost and performance.