Top Analytics Jobs in Richmond, VA

The Director, Research - Power Markets is responsible for leading the QA/QC process for long-term forecasting, advising leadership, and ensuring market insights are effectively integrated into forecasts.

Lead analytics for enterprise marketing and messaging: build data solutions and self-service tools, mine varied data sources, develop dashboards and BI insights, ensure data quality/lineage and governance, collaborate with tech teams on security and access, and monitor data quality.

The Senior Data Analysis Manager will manage data analytic projects, create dashboards, partner with stakeholders, and lead a team, focusing on strategic insights and analytics.

Lead a team of people analytics analysts to deliver talent acquisition and international strategy analytics. Own data standards, end-to-end projects, pipeline integrity, AI/automation prototyping, and executive reporting while coaching staff and translating technical insights into recommendations for senior leadership.

Lead analytics for Network Products & Platforms, turning network data into AI-enabled insights. Drive product analytics, operational planning, cross-functional coordination, people development, and data product strategy to improve payment network performance, reliability, and profitability.

The analyst will own planning for launches, build forecasting models, partner with stakeholders, and drive data-driven decisions using AI and analytics.

The Analyst I will own analytics workflows, drive improvements, build data models, and support business metrics while collaborating across teams.

The Analyst II will analyze data to optimize fraud strategies, develop machine learning models, and collaborate with teams to enhance product safety.

Designs, builds, and operates ELT data pipelines and analytical datasets for Platform Analytics. Curates and models source data into conformed datasets, ensures performance, reliability, and cost efficiency, contributes to target-state architecture, mentors junior engineers, and uses AI coding tools to accelerate development and delivery.

Lead analytics engineering for Revenue, Marketing, and Finance by building scalable data solutions, data models, and dashboards; provide training and consultation, support ad hoc data needs, and translate technical findings into executive-level insights to improve operational performance.

Design, build, and maintain scalable dimensional data models, semantic layer, and production transformation pipelines. Collaborate with Data Engineering, Data Science, BI, DevOps, and Product to enable AI-ready data, ensure data quality and governance, support ML feature delivery, and coach analytics team members for robust, production-ready data products.

Lead technical design and architecture for analytics engineering: build and govern the semantic/metrics layer, optimize dbt and Snowflake for performance and AI use cases, mentor engineers, partner with Data Science and Engineering, drive data quality, CI/CD, observability, and deployment of third-party data and emerging tooling to support analytics, ML, and agent-based products.

The Senior Data Engineer will design and implement scalable data models in BigQuery using dbt for analytics and reporting, ensuring data governance and optimal performance.

Lead and grow a team of analytics engineers while remaining hands-on with SQL, dbt, and Snowflake. Own roadmap and semantic layer development, build trusted, governed data products, partner with cross-functional stakeholders, champion data quality and observability, and hire and coach engineering talent to deliver scalable analytics and AI-ready foundations.

The Manager will lead payments governance and oversight initiatives, implement data reporting frameworks, and enhance risk management practices through stakeholder collaboration and data insights.

Lead Finance Data & Analytics to build trusted data sources, governance, and analytics for Finance and cross-functional stakeholders. Manage analysts, drive data strategy and Snowflake data models, produce insights via SQL and Tableau, and deploy AI solutions to optimize finance decision-making and operations.

Lead a team of analysts and data scientists embedded in sales to build rigorous pilot analyses, create executive-ready business cases, expand consultative analytics across the partner lifecycle, and publish industry insights while coaching and scaling the Solutions Analytics function.

Lead design and implementation of shared, reusable analytics data models and pipelines. Drive standardization, governance, observability, and CI/CD for analytics; partner with Data Science, Infrastructure, and Product to certify metrics, modernize orchestration, and integrate AI-native tooling.

The Business Director leads strategic initiatives using analytics to transform the associate experience and improve decision-making, collaborating with Tech leaders while mentoring junior team members.

This role drives data-driven decision-making in product analytics, collaborating with cross-functional teams to generate actionable insights and evaluate new launches to enhance platform growth.

Design, build, and maintain end-to-end data models and pipelines to support CX operations, compliance reporting, and customer insights. Create dashboards and metrics, enforce data quality and governance, automate recurring workflows, and partner with stakeholders and broader data teams to deliver self-serve analytics solutions.

Lead Card Technology Analytics to convert developer telemetry into executive insights, measure developer productivity, assess AI tooling impact, govern delivery health, model capacity and financial tradeoffs, and manage a cross-functional analytics team to drive tooling and process decisions.

Lead design and build of ETL pipelines and Gold Layer tables in Databricks; develop semantic layers, data dictionaries, and AI-ready documentation; create dashboards and ad-hoc analyses to surface marketing and sales KPIs; partner with stakeholders to translate requirements into analytics-ready datasets and enable self-serve BI and agentic AI workflows.

As a Forward Deployed Data Analyst, you will configure and implement data systems for clients, ensuring their analytics are accurate and actionable. You'll work with teams to refine metrics and improve data processes, ensuring value from day one.

Build and maintain production-grade data models and pipelines for the Compliance Data Mart, implement data quality frameworks and monitoring, partner with engineering to resolve data gaps, support regulatory exams and audits, and automate manual workflows into scalable pipelines and self-serve tooling.