Top Data & Analytics Jobs in St. Louis, MO

Build and maintain dashboards and reports (Excel, Tableau, Sigma) by pulling and modeling production data (SQL, Python). Create pricing models for RFPs, define operational and financial metrics, optimize queries and data structures, run A/B experiment analyses, and partner with business leaders to generate insights and recommendations to improve roadside assistance operations and performance.

Implement client revenue cycle data into company systems by creating and configuring ETL processes, building data transformations and logical/physical schemas, documenting solutions in Jira, attending client meetings, and mentoring team members to ensure post-implementation data integrity.

Lead and build PushPress's data and AI foundation: define data strategy, architect pipelines and warehousing, ensure data quality and governance, enable AI product features, deliver analytics and reporting, and hire and grow a high-performing data team.

Execute financial models and pharmacy claims analyses to support underwriting for sales bids, present results to stakeholders, recommend pricing adjustments, drive pricing research, improve processes, and run quality control on analyses.

Analyze on-chain trading activity and market/DEX/CEX data at scale, build models for portfolio/PnL and capital efficiency, design AI-driven research pipelines, produce insights to inform product and capital strategy, and collaborate with product and engineering teams.

The Senior Product Analyst will analyze complex data sets to guide product strategies, support game teams, and drive game performance insights through collaboration and robust reporting on game features.

Drive go-to-market revenue analytics and strategy by building forecasts, dashboards, and ad-hoc analyses. Partner with Sales, Sales Ops, and Finance to set targets, quota, and deliver actionable recommendations to executive leadership.

The role involves collecting, analyzing, and visualizing data for investment research, utilizing web scraping, data tools, and data science techniques.

Develop and maintain datasets for visualization and machine learning; automate data pipelines; partner with teams to build data products.

The Data Analyst role involves collecting, analyzing, and interpreting program data to support decisions and reporting, while ensuring data accuracy and security. Responsibilities include developing dashboards, identifying trends, and collaborating with teams.