Top Analytics Jobs in Richmond, VA

Lead data analytics strategy, mine and analyze large-scale datasets, build and validate models, improve reporting and operational processes, evaluate products and marketing initiatives, and consult on data systems. Manage and mentor junior analysts, collaborate across business units, oversee concurrent projects, and apply business intelligence tools to support customer experience and organizational decision-making.

Build and maintain dbt data models, SQL transformations, ingestion pipelines, orchestration, and Tableau dashboards in support of HR and enterprise analytics. Own data quality, metric standardization, privacy controls, Row-Level Security, documentation, CI/CD, and troubleshooting from source systems through reporting. Partner with stakeholders to define requirements and KPIs, support workforce forecasting, optimize BigQuery performance, and pilot AI-assisted analytics using Google Gemini.

Leads an eight-person analytics engineering team and sets strategy for trusted semantic models, governed data, enterprise BI, AI-powered data access, and production data applications. Oversees data modeling, evaluation datasets, telemetry, LLM routing, governance, security, and self-service capabilities. Partners cross-functionally to establish engineering standards, roadmaps, and measurable business impact while hiring, coaching, and developing team members.

Own marketing measurement from initial engagement through closed-won revenue. Manage cross-channel reporting tied to Salesforce pipeline, tracking across GA4, advertising platforms, SEO, and AI search. Validate multi-touch attribution, analyze marketing experiments, model budget impact, and recommend investment priorities. Present performance insights to marketing and sales leadership across global regions.

Evaluate enterprise data architectures, governance frameworks, integration patterns, ownership models, and data quality practices. Design target-state architectures supporting analytics and AI, define governance operating models, assess data flows, develop quality controls, and create strategic roadmaps and executive recommendations. Collaborate with business and technology stakeholders on data modernization, cloud migration, AI enablement, and enterprise data management initiatives.

Leads People Analytics enablement and BI strategy, overseeing semantic models, certified data products, metric governance, data foundations, advanced analytics enablement, demand prioritization, and adoption. Partners with People Analytics, IT, and HR Strategy teams to create trusted workforce data, reusable semantic assets, and decision-ready insights. Manages teams and operating models while driving data quality, governance, certification, self-service analytics, AI access, and scalable insight delivery across the enterprise.

Manage data governance and risk programs for Global Payment Networks. Analyze large datasets, build and validate models, improve data and reporting processes, establish controls, support privacy and regulatory compliance, and lead cross-functional projects. The role also includes mentoring junior analysts, managing concurrent initiatives, and consulting on data systems, product testing, and business intelligence solutions.

Build Deepgram’s governed decision layer above warehouse gold tables. Responsibilities include modeling cross-system entities, owning semantic and metrics definitions, creating agent-facing data tools and MCP surfaces, implementing data quality assertions and reconciliation checks, evaluating AI agent accuracy, and answering business questions while leaving reusable models behind. The role requires production-grade SQL and Python, semantic-layer ownership, strong data modeling judgment, AI-native workflows, clear writing, and comfort building infrastructure from scratch.

Leads enterprise analytical-tool validation, including framework refinement, project execution, methodology risk assessment, technical research, prototyping, and validation reporting. Partners with cross-functional leaders to influence business strategy, solves complex analytical problems, and coaches junior staff. Requires substantial data analytics, open-source technology, statistical modeling, and people-management experience.

Leads people analytics initiatives that support talent strategy and workforce decisions. Responsibilities include developing analytics frameworks, managing data projects, building AI-powered data products and self-service tools, analyzing workforce data, prototyping automation solutions, and delivering insights to HR stakeholders and senior leaders. The role also involves data strategy, dashboard development, project execution, and potentially people management.

Leads enterprise data and analytics strategy, architecture, modernization, and delivery across cloud and on-premises environments. Oversees data platforms, engineering, integration, governance, quality, lineage, security, and compliance. Partners with executives to define roadmaps and investments, manages cross-functional teams and vendors, enables AI/ML capabilities, and mentors data professionals while driving scalable, trusted data solutions and measurable business outcomes.

Designs and maintains scalable data infrastructure, ETL/ELT pipelines, canonical datasets, and AI context layers. The role improves data quality and alignment across sales and finance systems, investigates data inconsistencies, leads requirements through UAT and implementation, supports analytics self-service, and partners with cross-functional teams to deliver process improvements and reliable business data.

Manages programmatic analytics and insights for client accounts, leading measurement frameworks, brand lift studies, incrementality testing, and A/B experiments. Develops media and campaign strategies, communicates performance insights to clients, and supports pitches and QBRs. Oversees, mentors, and develops analysts while partnering with Product, Engineering, Sales, and Customer Success teams to improve measurement tools, campaign optimization, and analytical capabilities.

Owns fraud performance analytics for depository products, including monitoring losses, approval rates, false positives, customer friction, and risk metrics. Builds data models, transformation pipelines, dashboards, scorecards, and monitoring frameworks. Conducts fraud deep dives and develops optimized rules, policies, thresholds, models, and decision strategies. Partners with Product, Engineering, Machine Learning, Data Engineering, Fraud Operations, and Risk teams to improve fraud detection and support product launches.

Leads analytics strategy and technical delivery for clients, specializing in Adobe Analytics and Customer Journey Analytics. Conducts measurement workshops, defines KPI and implementation strategies, oversees tagging and data quality, guides experimentation, and reviews dashboards and insights. Advises senior stakeholders, manages and mentors consultants, supports proposals and account growth, and contributes to Adobe Experience Platform initiatives involving Target, RT-CDP, and AJO.

Apply strategic analytics to workforce planning, design evaluation frameworks for HR programs, develop tools and automated insights to retain and develop talent, prototype AI-first data solutions, and analyze internal and external workforce data to inform executive HR decision-making.

Leads project controls systems, reporting platforms, data governance, analytics, dashboards, and performance reporting. Integrates cost, schedule, risk, procurement, construction, and change data into unified reporting environments. Provides forecasting, trend analysis, and decision support to project leadership while driving automation and digital tool deployment. Coordinates requirements across clients, project management teams, engineering contractors, and construction contractors, and leads the project controls systems and analytics team.

Lead programmatic analytics for clients and internal teams by analyzing campaign and model performance, designing tests, developing measurement solutions, recommending optimizations, and presenting actionable insights. Partner with Sales, Customer Success, Product, Engineering, and clients to align marketing strategies, reporting requirements, and optimization efforts with business goals.

Build and operate trusted finance data products, pipelines, models, reconciliations, dashboards, and automation. Partner with Finance, Accounting, Data Engineering, Product, and Platform teams to resolve data issues, improve reporting, support financial close, establish data lake quality controls, and enable timely insights. Use SQL, Python, dbt, Spark, Airflow, and AI-assisted tools to deliver tested, traceable, production-ready solutions.

Lead and scale Runpod’s analytics and business intelligence function, managing analysts and BI practitioners while setting the analytics roadmap. Own core company metrics, consumption and marketplace analytics, self-service reporting, experimentation practices, and executive and board-level insights. Partner with Product, Finance, Engineering, Security, Supply, and Go-to-Market leaders to improve data quality, modeling, decision-making, and strategic outcomes.

Teaches online undergraduate and graduate data analytics courses, develops syllabi and lesson plans, prepares course materials, facilitates discussions, evaluates student work, provides feedback, and integrates responsible AI practices. The role requires maintaining course alignment with institutional objectives, supporting diverse learners, participating in faculty training, and applying current analytics methods, tools, and ethical data practices.

Build and maintain product data models, ELT pipelines, semantic layers, and self-service analytics assets. Partner with Product Engineering and Data Governance to define canonical data, certify metrics, document taxonomies, monitor data quality, and support expansion and upsell analytics. Translate business requirements into governed data products, communicate insights to technical and non-technical stakeholders, and ensure data tooling complies with federal frameworks including FedRAMP and DoD IL4/5.

Own commercial and growth analytics for GeneDx’s top line, answering questions about volume, revenue, pricing, coverage, field capacity, and product performance. Serve as a senior advisor to commercial and product leaders, structure ambiguous problems, lead analyses end to end using AI agents, communicate executive-ready insights, support evidence-based decisions, monitor outcomes, and surface emerging opportunities. Maintain analytical governance, apply measurement and experimental design, and contribute reusable methods to the analytics function.

Leads operational analytics for the Take 5 Oil Change network, translating transactional and market data into insights that improve sales, profits, volume, and shop performance. Responsibilities include complex analysis, KPI reporting, dashboards, executive presentations, operational initiative measurement, stakeholder collaboration, data-quality improvement, and mentoring analysts. The role requires strong Excel, SQL, financial modeling, communication, and multi-shop operations experience.

Leads analytics, reporting, data modeling, automation, AI-agent development, and quality assurance for revenue cycle operations. Creates Power BI and Excel reports, analyzes complex healthcare and operational datasets, develops scalable warehouse models, and delivers actionable insights to leadership. Uses SQL, cloud data platforms, Git, Python, and AI-assisted tools to improve reporting efficiency, accuracy, and decision support.