Top Data & Analytics Jobs in Richmond, VA

The Senior Manager of Data Analysis will manage validation projects, assess analytical tool risks, and mentor junior staff while collaborating cross-functionally and enhancing analytical capabilities.

Support Enterprise Data Risk Management by testing and validating data management controls, analyzing data to identify risks and trends, collaborating with stakeholders to assess and remediate gaps, and recommending improvements to data management practices, automation, and validations to advance data management maturity.

As a Senior Marketing Analyst, you will provide data-driven insights to drive marketing strategy, analyze campaign effectiveness, and manage analytics for B2B growth.

As a Data Analyst at Circle, you'll analyze payments data, create visualizations, develop dashboards, and support decision-making with insights. You'll partner with business teams to identify opportunities for enhancement and communicate findings effectively to stakeholders.

The Analyst II will analyze data to optimize fraud strategies, develop machine learning models, and collaborate with teams to enhance product safety.

The Senior Staff Data Engineer will design scalable data systems, lead technical direction, optimize data platforms, and ensure data quality and performance for Observability & Insights.

Lead strategic vision and execution of GitLab's data platform and analytics capabilities, focusing on AI-enabled self-service analytics and data governance.

Analyze auction data to identify performance drivers and risks, collaborate with commercial teams, and provide actionable insights to optimize DSP outcomes.

As a Data Operations Analyst, you will maintain and enhance Charge Integrity SaaS by utilizing SQL and data analysis to solve complex revenue cycle problems and ensure accurate charge capture.

The role involves building large, scalable analytics pipelines, defining data models, integrating data, and collaborating on data architecture and strategies.

Lead the data engineering team, develop and maintain data models and pipelines for risk domains, and manage data quality and governance.

As a Data Engineer II, you will build, scale, and optimize data platforms, focusing on ETL/ELT pipelines, and collaborate with data scientists and AI engineers to support data-driven applications and insights.