Top Senior Analytics Jobs in Richmond, VA

The Manager of Analytics oversees a team to deliver impactful analytics and insights, supports business decisions, and integrates AI applications in analytics. They also manage testing portfolios and develop actionable insights for marketing strategies.

The Senior Consultant will lead the design and implementation of data solutions using Microsoft Fabric, Power BI, and Databricks to enhance analytics capabilities for clients. They will engage with stakeholders to define data strategies and deliver high-quality consulting services across multiple projects.

Design, build, and maintain scalable Databricks-based data pipelines and ELT workflows; develop and document dbt models; define data modeling methodology; ensure data quality, reliability, and scalability; collaborate with clients and cross-functional teams; provide technical guidance and deliver improvements to clients' data infrastructure and analytics capabilities.

The Marketing Analytics Manager role involves managing marketing performance metrics, analyzing campaign performance, and collaborating with teams to optimize marketing investments and conversions.

This role involves conducting advanced data analysis to drive strategic decisions, defining metrics, collaborating with teams, and improving performance through insights.

As the Director of Analytics, you'll lead analytics for MyPrize, optimizing performance across teams, developing reporting tools, and informing data infrastructure.

The Senior Manager, Analytics & Insights will support sales and operational teams through advanced analytics and data-driven insights, focusing on GTM strategies and analytics infrastructure.

Lead the People Analytics function by developing AI tools, predictive models, and dashboards to enhance HR decision-making and employee experience.

Lead design and expansion of a unified analytics data platform integrating Medicare claims, clinical systems, and vendor feeds. Implement AI-augmented data engineering (LLM coding assistants, automated QA, autonomous data-quality agents), build validation/reconciliation/audit infrastructure, partner with analytics teams for reporting and modeling needs, and drive large-scale analytics platform and web app implementation while collaborating with IT on security and deployment standards.

The Director, Ecommerce and Marketing Analytics leads analytics across multiple business functions, transforms data into insights, governs AI workflows, and establishes analytical standards to drive decisions and actions throughout the organization.

Manage performance, reliability, and accountability for high-volume messaging programs. Build dashboards and alerting, run ad hoc analyses, coordinate incident response and vendor testing, conduct post-incident reviews, and maintain documentation and compliance tracking to inform program decisions and improvements.

Lead capacity planning and commercial analytics: build and maintain capacity reporting, dashboards, and NetSuite inventory processes; enforce data governance and KPIs; partner with Sales, Finance, and Operations to enable data-driven commercial decisions and scalable growth.

Lead Analytics Engineer responsible for end-to-end data solution design, evolving data architecture, mentoring engineers, driving data health and observability, enabling cross-functional measurement, and contributing to roadmap and decision-making.

Lead and build Harvey’s people analytics function: design the people data architecture, consolidate HR systems, define metrics and methodology, create dashboards and forecasting models, surface leading indicators for intervention, enable self-serve analytics, and partner with People Ops, Recruiting, Finance, and Data Engineering to drive strategic workforce decisions.

Lead revenue operations and business insights by owning GTM and revenue data integrity. Build reporting and AI-driven insights, run billable usage analysis, manage data flows with Fivetran/Salesforce/Sigma, investigate billing disputes, and translate data into actionable narratives for leadership.

Build end-to-end data and analytics features: ingest and model data, build transformations and pipelines, create client-facing dashboards and interfaces, and develop LLM-powered workflows to accelerate analysis and app development. Partner with stakeholders, perform exploratory analyses, and ensure data quality, observability, and maintainability while influencing data engineering strategy.

Design, support, and improve data analytics solutions (OAC and Power BI). Manage data ingestion, ETL, data quality, access, and documentation. Liaise with stakeholders, migrate dashboards from OAC to Power BI, and follow SDLC and project management practices.

Manage underwriting analytics, collaborate with cross-functional teams, drive operational improvements, and enhance training for underwriters.

As a Senior Data Scientist in Marketing Analytics, you'll partner with Marketing to solve problems, design data-driven solutions, lead experimentation, communicate insights, and operationalize solutions for business impact.

Analyze commercial data for sales, marketing, service and support to create metrics and insights for optimization. Collaborate with cross-functional teams to provide data-driven recommendations and manage business intelligence tools.

Lead and manage data science teams to build models and drive business solutions; oversee compliance analytics and ensure data quality.

The Senior Data Analytics Manager leads analytical initiatives for Student Success Center operations, translating operational needs into data-driven insights to enhance agent performance and student outcomes through frameworks and dashboards.

Lead a team of analysts in Fraud & Safety operations, defining KPIs, designing experiments, optimizing performance, and enabling data-driven decisions globally.

Lead people-analytics strategy for Talent Acquisition and Talent Development. Drive end-to-end analysis of complex workforce problems, deliver evidence-based recommendations to senior leaders, ensure data governance and quality, coach junior analysts, build metrics frameworks, and conduct benchmarking and external research to inform workforce strategy.

Own and improve the dbt modeling and semantic layers, implement CI/CD, tests, observability, and governance; build governed metrics for BI and AI consumption; partner with Data Engineering and Risk to stabilize pipelines and improve data quality and documentation.