Top Senior Data & Analytics Jobs in St. Louis, MO

The role involves leading data architecture strategies and driving innovation in data solutions while ensuring compliance with governance policies. Responsibilities include translating data requirements into technical plans, overseeing advanced data technologies, and fostering collaboration among stakeholders.

Provide analysis in support of geospatial intelligence missions, manage data dissemination, and develop workflows for data analysis and visualization.

The Data Analyst in Revenue Operations will analyze sales data, build models, and create reports using SQL, Excel, and BI tools to empower business decisions.

Lead the marketplace analytics by optimizing monetization strategies, monitoring performance, creating dashboards, and analyzing supply-demand dynamics. Collaborate cross-functionally to drive engagement and profitability.

As a Sr. Business Systems Analyst, you will enhance Salesforce and FinancialForce systems, manage business applications, and ensure SOX compliance while collaborating with cross-functional teams.

The Senior Portfolio Lead will oversee data management services for clients, ensuring quality deliverables, strategic oversight, and optimal clinical data flows, while leading cross-functional teams and managing complex client relationships.

The Director of Analytics leads Upstart's Credit Analytics team, driving credit forecasting, valuation, and risk capital. Responsibilities include setting vision, developing leaders, and enhancing analytical frameworks in collaboration with tech and finance teams.

The role involves assessing fraud program effectiveness, compliance with regulations, and providing strategic insights for risk management within the financial services industry.

The Principal GTM Analyst translates complex business questions into actionable insights, collaborating with Marketing and GTM teams to drive growth and marketing efficiency through advanced analytics and storytelling.

Lead the evolution of data platform by designing scalable pipelines, improving data processes, mentoring teams, and modernizing data architecture.