Top Analytics Jobs in Richmond, VA

Leads the architecture, design, and implementation of Azure-based analytics and data engineering solutions. Develops and optimizes data pipelines, ETL/ELT processes, query layers, Delta Lake solutions, and integrations across Databricks, Azure Data Lake, Synapse, Data Factory, and Power BI. Partners with stakeholders, oversees end-to-end delivery, ensures security and governance, documents data flows, and mentors data engineers while promoting scalable, high-quality solutions.

Leads a team delivering Customer Success reporting, dashboards, KPI frameworks, and operational analytics. Oversees reporting accuracy, data integrity, recurring metrics, workflow improvements, and automation. Partners with Customer Success and services leadership to translate business needs into analytical requirements, prioritize initiatives, standardize reporting methodologies, and communicate performance insights. Coaches analysts, manages workload and development, and supports data-driven operational decision-making and scaling.

Leads internal data analysis projects, identifies business opportunities and risks, delivers strategic insights to leadership, manages junior analysts, develops dashboards, and improves data quality across company platforms. The role requires translating quantitative findings for nontechnical audiences and applying healthcare or pharmaceutical dataset experience to strategic decision-making.

Serve as a strategic advisor to higher-education institutions using EAB's Edify platform. Translate institutional priorities into data strategy, drive adoption and change management, align technology and services, measure impact, and advocate partner needs across Product, Engineering, Sales, and Services.

Own Chamber’s central analytics and reporting function for value-based cardiology contracts and clinical programs. Build SQL models, governed metric definitions, a semantic layer, data-quality standards, executive and board reporting, payer deliverables, SLA tracking, and clinical analytics foundations. Establish reporting governance so finance, clinical, and operations teams can self-serve trusted insights. This hands-on player-coach role requires healthcare claims and clinical data expertise, value-based care fluency, and the ability to build a reporting function from scratch.

The Lead, Advanced Analytics, Acquisition will analyze data, define metrics, conduct A/B tests, and collaborate with teams to drive growth and insights.

Own client-facing analytics strategy and implementation across GA4, Adobe Analytics, tagging, measurement frameworks, dashboards, experimentation, and GEO measurement. Audit and QA analytics implementations, define KPIs, evaluate incrementality and causal relationships, present executive-ready insights, and collaborate with SEO, paid media, creative, data, engineering, and client teams. Build AI-assisted workflows, automations, scalable tools, and dashboards while mentoring teammates and managing multiple client workstreams.

Leads and scales a global data engineering and analytics team while remaining hands-on with architecture, pipelines, data quality, dimensional modeling, dashboards, reporting, and customer-facing deliverables. Owns the analytical data platform supporting clinical, operational, product, financial, and customer data. Partners with cross-functional stakeholders, investigates complex data issues, improves platform reliability and security, and mentors engineers.

Conduct quantitative research for traders by testing market hypotheses, building and maintaining documented signals, performing event studies and backtests, and validating results against leakage, survivorship bias, transaction costs, and regime dependence. Organize reproducible point-in-time datasets, communicate findings clearly, track signal performance, and use AI tools to accelerate research and coding while verifying outputs.

The Analytics Architect will design and implement cloud-based analytics solutions, maintain data pipelines, ensure data quality, and collaborate with teams to enhance operational efficiency.

Leads Magellan Health’s enterprise data and analytics strategy, modernization, engineering, governance, business intelligence, and AI/ML enablement. Oversees data platforms, pipelines, quality, lineage, compliance, and reporting while partnering with clinical, operational, and financial stakeholders. Builds and develops a 30+ person organization, manages a $3M–$5M budget, oversees vendors, and presents investment cases to executive leadership. Drives transformation from a low-maturity environment to a governed, insight-driven enterprise data platform.

Leads enterprise analytics engineering by establishing statistical standards, validation and QA practices, measurement frameworks, reporting standards, governance, reusable data pipelines, automation, and production-grade analytics solutions. Connects Commercial, Medical, Market Access, and other teams to enable scalable, trusted, compliant, and decision-focused analytics. Requires strong technical and cross-functional leadership, analytics infrastructure expertise, and the ability to build enterprise capabilities from ambiguity.

Own enterprise analytics audits, implementations, data quality, attribution, segmentation, SQL analysis, BI dashboards, experimentation measurement, and client reporting. Serve as the senior analytics partner for major accounts, present insights to executives, train client and internal teams, and help define analytics and experimentation services. The role requires hands-on Adobe expertise, autonomous prioritization, technical collaboration, and the ability to connect organic and AI search performance to pipeline and revenue.

Build and maintain CS reporting, dashboards, and health score models to identify renewal risk and inform strategy. Deliver executive reporting, collaborate cross-functionally to improve data quality, and develop predictive analytics and longitudinal tracking to reduce churn.

Lead design and implementation of scalable data models and analytical tooling for Consumer Product. Partner cross-functionally to translate business needs into reliable SQL/Python data products, dashboards, and automated pipelines using engineering best practices (CI/CD, testing, version control, monitoring). Drive data-informed strategy and manage long-term infrastructure while supporting ad hoc requests.

The Analytics Engineer will design and implement analytics solutions, maintain reporting dashboards, partner with Product on KPIs, and support marketing with analytics.

Lead the design and implementation of algorithmic trading strategies, oversee technical infrastructures, and mentor a multidisciplinary team while managing performance analysis and risk.

The Databricks Architect will design and implement large-scale data solutions, optimizing performance and reliability, while leading initiatives in data engineering.

The Senior Analytics Engineering Manager will oversee analytics engineering vision, manage a team, ensure data quality, and drive data-driven decisions across departments.

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.

Lead design, development, and migration of enterprise SAP BW solutions to SAP Datasphere; architect hybrid data flows with Microsoft Fabric and Azure Synapse; integrate BW with Salesforce and SQL Server; embed AI (Copilot, Azure OpenAI) into analytics; manage deliverables, mentor offshore teams, enforce standards, and ensure data integrity and performance for reporting and analytics.

Manages reporting and analytics operations, teams, workflows, critical business intelligence reports, and performance metrics. Leads data process improvements, requirements analysis, systems development, testing, reporting projects, and process re-engineering. Uses SQL, data warehouses, QlikView, Tableau, and related tools to support operational, financial, quality, compliance, and strategic decisions. Mentors staff, manages priorities, monitors risks, and partners with business leaders and clients.

Execute underwriting and case-valuation analytics: write and optimize SQL, build dashboards, maintain valuation models, forecast case outcomes, monitor portfolio performance, and translate insights for operational and marketing stakeholders.

The Data Architect will design scalable data models, transform raw data into actionable insights, and deploy analytics solutions for healthcare providers, with a strong emphasis on SQL proficiency and cloud technologies.

The Senior Analytics Engineer will design and build scalable data pipelines using dbt and Snowflake, providing technical guidance, conducting audits, and mentoring junior engineers while leveraging AI tools to enhance productivity.