Top Data & Analytics Jobs in Richmond, VA

As a Senior Lead Data Engineer, you will design, develop, and support data solutions, optimize systems, and collaborate within Agile teams to leverage technology for business transformations.

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 Data Scientist will build analytics infrastructure, conduct analysis and modeling, and collaborate with teams to enhance data impact and insights. Responsibilities include exploratory analysis, model building, and maintaining datasets for student success and operational efficiency.

The Senior Analytics Engineer will design and implement scalable data solutions for Finance Analytics, reconcile data accuracy, and collaborate across teams to enhance financial datasets and reporting workflows.

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

As a Senior Data Engineer, you will design and maintain scalable data models, build production data pipelines, and support analytics across various business functions.

The Director, Product Analytics & Strategy will lead market expansion, define product strategy, analyze market opportunities, and drive cross-functional collaboration to shape product direction and company growth.

The Senior Data Analyst collaborates with People teams to transform HR data into insights, conducts analyses, and builds dashboards to improve workforce effectiveness.

Lead design and implementation of shared, reusable analytics data models and pipelines. Drive standardization, governance, observability, and CI/CD for analytics; partner with Data Science, Infrastructure, and Product to certify metrics, modernize orchestration, and integrate AI-native tooling.