Top Senior Data & Analytics Jobs in Richmond, VA

Lead GTM strategy and analytics to build headcount/capacity models, territory optimization, quota setting, predictive models, and BI reporting. Partner with Sales, Marketing, Finance, and Data to inform planning cycles, monitor pipeline and productivity, and deliver executive-level insights for growth and investment decisions.

Lead development of the dbt semantic layer and analytics products, own data modeling and metrics, ensure data quality and documentation, support embedded analytics and AI initiatives, and partner with engineering, product, and partners to make data trusted and accessible.

Serve as the analytics bridge between marketing/operations and data teams: translate business questions and KPIs into clear product requirements, own delivery of treated tables, semantic layers, reports and dashboards, align stakeholders on a single source of truth, run gap analyses, document processes, and ensure delivered data products drive decision-making and adoption.

Support a core set of clients by guiding users on Numerator's Insights platform, performing ad-hoc/custom analyses using proprietary consumer panel data, delivering actionable analytic insights and recommendations, and presenting findings across channels including industry forums and written content.

Lead actuarial analyses for value-based care, forecasting Medicare risk and financial performance using large claims and EHR datasets (CCLF, BCDA). Build SQL data structures, IBNR and risk score projections, create executive dashboards, support budgeting, and ensure regulatory compliance under CMS/CMMI programs.

Serve as a senior advisor on enterprise data architecture and Adobe Experience Platform. Lead client discovery, design XDM schemas and identity resolution, guide data ingestion/ETL, governance, and Customer 360 initiatives. Provide technical leadership, mentor teams, review architecture, and contribute templates and best practices across consulting engagements.

Build and maintain scalable ETL/data pipelines and internal frameworks to support ML and product teams. Drive architecture, observability, data quality, and engineering best practices across AI/ML workflows and prompt-engineering pipelines.

Build governed gold-layer data models and a single-source metrics layer in Snowflake (dbt); create and optimize dashboards in enterprise BI tools; use AI coding agents and AI-assisted tooling to accelerate development; ensure data quality, governance, and consistency; collaborate with data engineering and stakeholders to deliver trusted analytics for internal and client-facing use.

Client-facing BI consultant responsible for end-to-end delivery of TARGIT-based analytics: requirements gathering, prototyping, backend work, dashboards, training, deployment, optimization, and customer engagement.

Lead enterprise data strategy and governance, build AI-ready data infrastructure and BI systems, own SharePoint platform, partner cross-functionally to ensure data quality, access, compliance, and user adoption.