Top Data & Analytics Jobs in Richmond, VA

As a Senior Data Scientist, you will develop statistical models and machine learning algorithms to improve patient enrollment and trial management while ensuring compliance in a healthcare data environment.

Lead technical design and hands-on development of Pantheon’s data platform, extending ingestion, curation, retention services and ML/LLM infrastructure. Mentor engineers, drive architecture and engineering standards, operate in a DevOps model, partner cross-functionally, and participate in on-call support to ensure reliable, compliant data access and analytics.

Lead analysis of business processes, gather and document requirements, design and implement system solutions, support deployments, and create reports/dashboards. Collaborate with stakeholders and IT to improve systems, provide user training, and perform post-implementation reviews to enhance performance and efficiency.

Design, implement, and maintain dbt/Snowflake ELT transformations to convert raw clinical and multimodal health data into trusted, analysis-ready models; enforce data quality, lineage, testing, CI/CD, and documentation; collaborate with clinical and ML teams to harmonize ontologies and support de-identification and ETL across health systems.

Lead measurement and insights strategies across B2B client programs. Analyze earned/social/web data, conduct secondary research, build measurement frameworks and dashboards, deliver client-facing recommendations, mentor junior staff, and advance agency analytics capabilities.

Design, build, and maintain automation workflows and data pipelines across admissions, education, career services, and billing. Create BI dashboards, ensure data accuracy, manage lightweight databases (e.g., Supabase), and support cross-functional teams to improve operational efficiency and scalability.

The Senior Data Engineer will design and build scalable data platforms, handle automation for data operations, and ensure reliability and performance of data pipelines while collaborating with various teams.

The job involves leveraging AWS and Snowflake for data engineering tasks within a technology-focused company, requiring US residency.

Own and optimize data infrastructure and ETL/ELT pipelines using SSIS and Microsoft Fabric. Build and maintain SQL Server data warehouse staging, transformations, and lakehouse ingestion. Implement CI/CD, version control with GitHub, monitor pipeline health, troubleshoot data issues, document data flows, and translate stakeholder requirements into data engineering solutions that support BI reporting.

The Product Analyst will design experiments, analyze user behavior, and communicate insights to drive engagement and retention decisions effectively.