Top Senior Data & Analytics Jobs in Washington, DC

Perform complex data exploration and manipulation across large datasets to generate customer and digital-product insights. Design and analyze experiments, track campaign performance, build BI solutions, partner with stakeholders and product teams, maintain data quality and controls, and mentor junior analysts.

The Regulatory Data Technical Advisor will support BARDA's R&D efforts by ensuring compliance with nonclinical data standards and managing dataset quality control for medical countermeasures.

Analyze and document claim and encounter data, write complex SQL queries and reports, perform root-cause analysis, support system enhancements, execute test scripts, and collaborate with stakeholders to deliver data-driven solutions for healthcare claims/encounters.

The Supply Chain Analytics Manager gathers and analyzes data to drive insights, creates dashboards, and establishes data practices for informed decision-making.

Lead analytics projects using advanced and predictive modeling to optimize programs, forecast behavior, and drive revenue. Partner consultatively with business, IT, and SMEs across project lifecycle—intake through delivery—communicating results to stakeholders and senior leadership. Work independently on complex technical approaches and influence department strategy.

Lead architecture and implementation of enterprise-scale, production data pipelines and ecosystems for global, customer-facing products. Collaborate with product and engineering leadership, mentor peers, enforce code and CI/CD standards, and optimize data storage and performance for high-availability, defense-focused monitoring solutions.

Lead development and execution of measurement and insights strategies for B2B clients. Analyze earned/social/web data, conduct secondary research, build measurement frameworks and dashboards, present strategic recommendations, mentor junior staff, and partner with cross-functional teams to drive campaign performance and business impact.

Design, build, deploy, and maintain scalable data pipelines and platforms. Integrate and analyze structured and unstructured data from APIs and databases, guide cross-functional teams, and apply data mining, statistical analysis, and AI/ML to support mission-driven projects.

Conduct theoretical and empirical research in mortgage finance; develop and validate statistical, econometric, and predictive models; analyze large structured and unstructured datasets using Python/SAS/R/SQL; implement model validation and testing; interpret results within business context; communicate findings to technical and non-technical stakeholders; collaborate with cross-functional teams and apply new technologies including AI to improve analytics and business performance.

Lead architecture, implementation, and optimization of scalable data platforms, ETL/ELT pipelines, and data governance. Ensure security and compliance, mentor junior engineers, drive CI/CD and IaC for data workflows, and collaborate with stakeholders to deliver actionable analytics and reporting.