Top Analysis Reporting Jobs in Richmond, VA

Design and run evaluation frameworks to assess third-party vendor data for fraud detection. Build lift analyses, backtests, and champion/challenger tests; profile vendor datasets for quality and coverage; collaborate with fraud, product, and data engineering to define ingestion and testing requirements; translate findings into actionable recommendations and maintain an internal knowledge base; support ad hoc analyses on fraud trends and model performance.

The Senior Data Analytics Engineer will develop data pipelines, support data-driven decision-making, collaborate with stakeholders, and improve data quality and processes.

The Senior Data Scientist will build frameworks for data-driven decision making, develop predictive models, ensure data quality, and enhance customer experiences through analytics and operational insights.

As a Data Engineer, you will develop and manage data pipelines, ensuring reliable data ingestion and delivery while optimizing for simplicity and performance.

The Senior Data Engineer will develop data engineering solutions, manage ETL workflows, and establish a new data practice while collaborating with stakeholders.

The Senior Technical Analyst collaborates with stakeholders and engineers to document requirements, ensure quality, and support SDLC activities, while being a trusted advisor on solution design and process impacts.

As an Analytics Lead, you will manage the measurement strategy, oversee tracking architecture, design testing frameworks, and create insights for clients. You'll lead a junior specialist and ensure data integrity across client accounts. Responsibilities include building dashboards, interpreting metrics, and creating measurement plans to drive business decisions.

The IBM TM1 Developer will manage the SDLC for Finance applications, focusing on TM1 and migrating from Essbase, while collaborating with global teams.

Design and deliver Databricks-centric data architectures, lead pre-sales and billable engagements, build end-to-end data engineering pipelines for AI/ML and BI, mentor teams, ensure data governance/security/quality, and resolve data system issues while producing solution documentation and presentations.

Lead client-facing Collibra implementations across data governance, metadata management, catalogs, glossaries, workflows, and stewardship. Facilitate discovery and design workshops, translate requirements into scalable Collibra designs, configure and develop platform capabilities, drive integrations and testing, and coach client teams for adoption and sustainment.