Top Analytics Jobs in Richmond, VA

Leads data strategy for MetLife’s Group Benefits business by connecting business and Data & Analytics teams, establishing shared definitions, resolving ownership gaps, and improving governance and quality. The role leads Data Councils, supports Agile Release Trains, removes data-related blockers, and strengthens data foundations for decision-making, service delivery, analytics, and AI initiatives.

Analyze AML investigation volumes, risks, productivity, capacity, KPIs, and financial contributions. Develop analytical recommendations, optimize investigative operations, support modeling and strategy, and lead implementation and monitoring efforts. Partner with IT, Sales, Operations, Finance, and other teams to improve quality, service, volume, and profitability while supporting AML defenses and law-enforcement investigations.

Own product analytics strategy for a retail banking product, influencing roadmap and investment decisions through experimentation, causal inference, statistical modeling, and KPI frameworks. Query and transform large datasets using SQL, Python, or R; design and analyze A/B tests; identify growth opportunities; and communicate actionable insights to Product, Engineering, Finance, Research, and executive stakeholders.

Manage data analytics for PULSE Risk & Compliance by analyzing large datasets, identifying transaction anomalies and risk exposure, validating models, improving reporting and processes, and supporting compliant data strategies. The role involves Python-based programming, BI, database and data-storage design, strategic testing, cross-functional collaboration, project leadership, and people management in a hybrid environment.

Analyze complex data to support business decisions, build self-service data solutions, develop dashboards and metrics, and improve data quality and governance. The role uses Python, R, Spark, SQL, AWS, business intelligence tools, and data management practices while partnering with business and technology teams on analytics and transformation initiatives.

Leads data analytics strategy, modeling, testing, reporting, and process improvements across business units. Mines complex databases, evaluates products and processes, improves operational efficiency, and consults on data systems. Manages and mentors junior analysts while supporting projects through the full lifecycle. The role emphasizes business intelligence, programming, strategic analysis, and collaboration in a fast-paced environment.

Leads strategy, planning, and execution of customer EMR integrations for PhareOS. Oversees end-to-end data delivery, integration quality, process standardization, tooling, vendors, and platform enhancements. Builds and scales the data integration team, manages resources and senior client stakeholders, and drives innovation across integration methods and operating models. Requires extensive healthcare data integration leadership, HL7/FHIR and interface engine expertise, SQL proficiency, and strong program management skills.

Own Eve’s go-to-market data models and semantic layer for governed metrics including pipeline, conversion, CAC, win rate, ARR, and bookings. Establish certification frameworks, modeling standards, documentation, alerting, and analytical application patterns across the organization. Partner with Sales, Marketing, Customer Success, and RevOps stakeholders, resolve conflicting metric definitions, enable AI-grounded data tools, review contributions, and mentor analytics engineers.

Analyze and optimize drug pricing using data-driven models, dashboards, reports, and strategic frameworks. Partner with Sales, Operations, Marketing, Finance, Product, pharmacy partners, and data teams to identify opportunities, define success metrics, improve reporting, and balance pharmacy economics with patient affordability. Serve as a trusted analytical advisor and support backend data development and query optimization.

Leads enterprise data governance strategy, transformation, operating model modernization, accountability, and executive engagement. Partners with senior stakeholders to improve data trust, accessibility, regulatory alignment, risk management, analytics, AI readiness, and business outcomes. Represents the Data Office in strategic and regulatory forums, establishes roadmaps and performance measures, resolves cross-functional data challenges, and drives organizational change without direct authority. The role focuses on governance and transformation rather than engineering, coding, analytics delivery, or technical administration.

Leads a client-facing healthcare analytics team that designs and maintains prior authorization decision automation programs. Consults PaaS clients, develops strategic roadmaps, translates requirements into technical blueprints, analyzes authorization and claims data, and builds KPI reports using visualization tools. Manages direct reports, improves analytics processes and AI tooling, partners with product and engineering teams, and ensures automation outcomes and client KPIs are achieved.

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.

Own Hometap’s product and marketing event-data ecosystem, including taxonomy, tracking plans, governance, Segment Protocols, schema validation, and source management. Partner with marketing, product, and engineering to define instrumentation and event specifications. Build monitoring for schema conformance, event volume, and property completeness, while documenting standards and managing event review and deprecation processes.

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.

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.

Owns the CX Operations data foundation in Snowflake by designing architecture, governance, data quality standards, and reusable dbt models. Leads complex analyses, dashboards, scenario planning, and executive communication while mentoring analysts and partnering with engineering and strategy teams. Supports AI enablement by creating trusted data models, evaluation standards, and agent performance tracking.

Build and maintain SQL and dbt data models, tables, views, dictionaries, and self-service tools on BigQuery. Support Accounting, Actuarial, and Claims stakeholders from request through production, monitor data quality, prevent defects, document processes, and review AI-generated code. The role requires hands-on data development, collaboration across projects, and growing ownership of a data domain and stakeholder relationships.

Build and maintain dbt transformation models and Power BI semantic layers on Microsoft Fabric. Establish data quality testing, observability, governance, CI/CD, documentation, and access controls. Partner with business and technology stakeholders to define reliable metrics and data products, optimize performance and costs, troubleshoot issues, and mentor analysts and engineers while advancing analytics engineering standards.

Leads Merakey’s enterprise data, analytics, AI, integration, governance, and business intelligence strategy. The Vice President will establish data architecture, governance, master data management, reporting, and advanced analytics capabilities across clinical, operational, financial, and workforce functions. Responsibilities include supporting acquisitions, integrating disparate platforms, developing responsible AI practices, managing vendors, shaping the data operating model, and building high-performing teams. The role partners closely with the CEO, CIO, executive leadership, and business stakeholders to drive enterprise transformation and data-informed decision-making.

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.

Build and maintain dbt-based data transformations, analytics models, ELT workflows, testing, and data quality processes. Collaborate with analysts, engineers, and stakeholders to support reporting, self-service exploration, governance, and business decision-making. Troubleshoot data issues, document workflows, evaluate analytics tools, and contribute to scalable data practices using a modern cloud data stack.

Designs and maintains executive dashboards, reports, semantic models, and automated analytics solutions using Power BI. Defines enterprise KPIs, data standards, and business rules while integrating data from ERP, CRM, manufacturing, SQL, and cloud systems. Partners cross-functionally with senior leaders to deliver insights, improve data quality, support master data management, and enable scalable self-service analytics and data-driven decision-making.

Manages a business analytics team that delivers insights, KPI reporting, trend analysis, data visualizations, governance, and actionable recommendations. Guides statistical analysis, data modeling, querying, experimentation, and self-service analytics while aligning practices with enterprise standards. Partners with leaders to identify opportunities and risks, improve data quality, drive analytics adoption, and support strategic and operational decisions. Oversees team performance, department projects, communications, and best-practice development.

Leads global people analytics and workforce intelligence strategy, building AI-driven tools, predictive models, dashboards, and decision-support applications. Partners with IT, data, and security teams on governance, privacy, and ethical AI. Advises executives, democratizes workforce insights, measures people-program ROI, and anticipates talent trends through benchmarking and workforce modeling.

Lead advanced analytics for Airbnb’s host incentive programs. Own measurement strategy, design and analyze experiments, apply statistical and causal methods, develop metrics and reporting tools, and analyze complex datasets. Partner with Operations, Data Science, Finance, and Product leaders to deliver actionable insights, evaluate incrementality and ROI, and guide program decisions. Present recommendations to senior stakeholders and use AI-assisted analytics to automate repetitive work.