Top Analytics Jobs in Richmond, VA

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.

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.

Leverage data analytics, business intelligence, and Python to deliver strategic insights and tailored solutions for clients. Build reports, dashboards, data pipelines, and support data architecture and quality initiatives. Analyze data from multiple sources to identify trends, improve operations, and inform decision-making. Collaborate with stakeholders and team members while continuously developing technical skills and contributing to process improvements.

Leverage data analytics, business intelligence, and data science techniques to deliver strategic insights and solutions for clients. Build reports, dashboards, data pipelines, visualizations, and data architecture using tools such as Oracle BI, QlikView, Spotfire, and BIRT. Ensure data quality, manage stakeholder relationships, improve analytics processes, interpret complex datasets, and mentor junior team members while contributing to client projects and business strategy.

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.

Leads the strategy, architecture, implementation, and evolution of enterprise analytics platforms. Responsibilities include designing scalable data platforms, integrating digital and enterprise data, establishing governance and security standards, optimizing analytics and BI capabilities, evaluating cloud technologies, managing platform performance and risks, and mentoring technical teams. The role also requires close collaboration with executives, clients, Product, Engineering, Data Science, Marketing, and business stakeholders.

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.

Design and maintain analytical data models, transformation frameworks, data-quality checks, semantic definitions, and metric consistency across analytics and customer-facing products. Partner with engineering, product, and analytics teams to document data, improve lineage, and enable trustworthy self-service data usage. The role requires advanced SQL, analytics engineering, dimensional modeling, testing, and collaborative translation of business concepts into precise data definitions.

Leads analytics for Pricing and Supply, managing a team of approximately eight analysts. Partners with cross-functional leaders to prioritize analytical work, build dashboards and decision frameworks, improve metric quality, and generate insights into pricing, supplier coverage, marketplace performance, conversion, margin, and customer behavior. Coaches analysts, establishes scalable analytics processes, and collaborates with data engineering teams to improve data models, tooling, and self-service capabilities.

Leads a 15+ person analytics organization supporting Growth, Sales, Marketing, and Finance. Owns the analytics strategy, operating model, metric governance, executive reporting, forecasting, experimentation, customer and revenue insights, and data foundation improvements. Partners with senior commercial and financial leaders to translate complex data into strategic recommendations and builds scalable processes, systems, and talent development programs.

Leads business analytics strategy, data infrastructure, product analytics, measurement frameworks, experimentation, and data-driven strategy for AI-powered customer assistance channels. Connects customer experience and operational efficiency outcomes while partnering with Product, Technology, Operations, and Finance. Manages and develops analysts, oversees concurrent projects, builds business requirements, and drives executive-level decisions supporting growth, profitability, and service improvements.

Leads data governance, risk mitigation, analytical tool validation, and program development for Global Payment Networks. Responsibilities include planning validation projects, assessing analytical methodologies and tool risks, researching industry practices, preparing reports and presentations, and coaching junior staff. The role requires managing concurrent projects and applying data analytics, risk management, statistical, and project management expertise to develop enterprise-wide controls and processes.

Build AI-augmented BI dashboards, semantic layers, and AI-ready metadata. Use AI-assisted tools to accelerate SQL and dashboard development, productionize ML outputs into BI, enforce data quality and governance, and present insights to business stakeholders including C-suite.

Own end-to-end data products, including source onboarding, API and file-feed ingestion, orchestration, incremental and idempotent pipelines, Snowflake and dbt Cloud modeling, testing, documentation, alerting, and production reliability. Establish engineering standards, manage secrets and governance, use AI coding tools responsibly, collaborate with vendors and stakeholders, and mentor junior engineers.

Leads data analytics and business intelligence strategy, mining large datasets, building and validating models, improving processes and reporting, evaluating products and initiatives, and consulting on data systems. Manages and mentors junior analysts, collaborates across business units, and oversees projects from inception through completion. The role requires advanced analytical, programming, communication, leadership, and problem-solving skills.

Develop and maintain dashboards, reports, scorecards, KPI solutions, and analytical models that provide business performance insights. Responsibilities include trend and root-cause analysis, forecasting, data validation, stakeholder requirements gathering, reporting automation, process improvement, documentation, and data quality governance. The role partners with cross-functional teams and communicates findings to technical and non-technical audiences.

Develops and maintains production-grade analytics applications, dashboards, datasets, ETL processes, and enterprise analytics content. Designs database queries, performs testing and code reviews, maintains repositories and documentation, responds to incidents, and supports analytics tools. Provides user support, training, mentoring, and requirements gathering while collaborating with agency analytics and information services teams. The role uses tools such as R, Shiny, Python, Tableau, SQL, Git, and related business intelligence platforms.

Build and maintain cloud cost monitoring, alerting, and optimization tooling. Develop automation, cost allocation/tagging, data pipelines, dashboards, and integrations with billing APIs. Support FinOps processes, implement cost guardrails, troubleshoot cost systems, participate in on-call rotation, and collaborate with senior engineers and product teams to drive cost-efficient infrastructure and reporting.

Lead revenue analytics by developing business cases, dashboards, KPI frameworks, experiments, and automated analytics solutions. Partner with client success, marketplace, merchants, and cross-functional teams to evaluate performance, guide go-to-market decisions, quantify product value, and scale data-driven execution. Serve as the analytics subject matter expert while translating structured and unstructured data into actionable recommendations and compelling stakeholder narratives.

Lead end-to-end analytics for major platform partnerships, identifying growth opportunities and informing product, investment, risk, and pricing decisions. Conduct complex analyses, design experiments, build scalable data models, metrics, dashboards, and AI-assisted workflows, and translate findings into business recommendations. Partner cross-functionally with Product, Engineering, Finance, Revenue, and Strategic Partnerships while mentoring analysts and improving analytical practices.

Lead an analytics team to drive strategy for Accounts Payable and Expense Management. Translate customer, product, and financial data into insights, models, and experiments to inform product, pricing, marketing, and credit risk decisions. Partner cross-functionally to deliver business requirements, manage projects, mentor analysts, and measure impact to grow profitability and customer outcomes.

Lead end-to-end COGS and gross margin analysis for hardware and software products, model cost-saving scenarios, answer ambiguous executive questions, partner with data engineering/finance/product, build reliable datasets and analytical frameworks, and present recommendations to C-suite stakeholders.

Analyze complex data, build self-service data solutions, and develop business intelligence tools, metrics, dashboards, and visualizations. Partner with business and technology teams to deliver strategic insights, manage data quality, metadata, lineage, definitions, security, and access governance. The role requires scripting, data querying, Snowflake development, business intelligence visualization, and experience with data management and governance.

Leads project controls systems, reporting platforms, data governance, dashboards, analytics, and reporting automation. Integrates cost, schedule, risk, procurement, construction, and change data to support forecasting and project decision-making. Coordinates system requirements across clients and contractors, drives digital project delivery improvements, and manages the project controls systems and analytics team.