Top Data & Analytics Jobs in St. Louis, MO

The Business Intelligence / Data Analyst will optimize the data reporting pipeline using Google Big Query and Omni, work with product management, implement reports, and conduct ongoing maintenance.

The Data Engineer will design and maintain scalable data pipelines, automate workflows, and enhance data governance while collaborating with cross-functional teams.

Design, build, and maintain forecasting and portfolio optimization models for U.S. power markets; analyze market outcomes, track supply/demand/congestion dynamics, and apply statistical, optimization, and ML methods to inform commercial decisions.

As a Data Engineer, you will develop solutions for customer-centric technology, ensuring platform integration and managing data architecture. Responsibilities include building data processes, maintaining data integrity, and collaborating cross-functionally to meet business challenges.

As a Senior Machine Learning Engineer, you'll build and deploy ML models for risk and fraud detection, leading technical efforts and collaborating cross-functionally.

The GTM Analytics Engineer will enhance data usage across the revenue organization by refining models, designing workflows, automating processes, and partnering with teams to improve GTM strategies.

The Senior Value Attainment Analyst will analyze customer data to create ROI analyses that support renewals and expansions, ensuring accurate methodologies and compelling presentations for health system leadership.

The DMS Data Engineer is responsible for analyzing raw data, building data systems and pipelines, conducting complex data analyses, and collaborating on projects to enhance data quality and reliability.

As a Senior Staff Decision Scientist, you will optimize payment decisioning strategies, analyze risk data, and collaborate to improve platform performance and user experience.

The Data Engineer Consultant will design and implement scalable data solutions, advise clients on optimizing data environments, and develop ETL pipelines and data models to support business objectives.