Top Senior Data & Analytics Jobs in Richmond, VA

The Senior Analyst will support the personalization algorithm by conducting analyses, testing features, managing projects, and collaborating with teams to improve food recommendations for customers.

The role involves architecting and improving data systems, defining governance standards, optimizing performance, and mentoring engineers in data engineering.

Lead and grow a data engineering team that builds and operates ingestion, transformation, orchestration, and serving layers and a self-serve analytics substrate. Own data quality, observability, cost efficiency, SLAs, and engineering practices while partnering with Data Science, BIE, Analytics, and Product to deliver reliable, reusable data products.

Owns end-to-end Collections and Recovery reporting and analytics, translating operational needs into SAS-based data processes, Tableau dashboards, validated datasets, and leadership-ready insights. Responsibilities include requirements gathering, data quality controls, trend analysis, automation, reporting governance, stakeholder partnership, and responsible use of AI. The role also mentors analysts and supports scalable, forward-looking performance measurement within a regulated financial services environment.

Lead and grow the Revenue Analytics team to deliver strategic sales and customer lifecycle insights. Build forecasting, pipeline, capacity, predictive models, and customer lifecycle analytics to improve revenue, retention, adoption, and expansion. Partner with GTM, Finance, Product, and Enterprise Data to create executive reporting, data governance, AI-enabled self-serve datasets, and integrated analytics that drive business outcomes and support a shift to consumption-based models.

Own Silver and Gold medallion-layer modeling and semantic layer governance using dbt and SQL. Improve warehouse performance and cost, standardize BI tooling, collaborate with stakeholders to produce trusted metrics, troubleshoot data quality, and evolve analytics platform.

Partner with People teams to turn HR and org data into actionable insights. Build complex queries, statistical analyses, dashboards, and a centralized people data repository. Drive data governance, data quality, and stakeholder communication to support hiring, retention, productivity, and workforce decision-making.

Owner of the analytics foundation: design and maintain BigQuery/dbt models, pipelines, and Looker Studio reporting; build AI workflows and web apps on GCP; integrate marketing, e-commerce, and fulfillment data; ensure GCP ops, security, and reliability; use AI-assisted tools daily and collaborate with business and client stakeholders.

Translate business needs into clear data requirements, design and maintain curated integrated datasets, validate mappings and lineage, support data governance and quality, enable data products for reporting and analytics, and lead small data integration and process-improvement initiatives across business, analytics, and engineering teams.

Lead the development, refinement, validation, and communication of commercial real estate econometric forecasting models. Monitor forecast accuracy, conduct quantitative research, develop new models, improve data and methodologies, document processes, create dashboard inputs, and educate internal teams and customers on forecast results and model validation.