Top Analysis Reporting Jobs in Washington, DC

The Business Analyst will review medical records, submit appeals to insurers, analyze data, prepare reports, and lead projects.

The Data and Performance Analyst will manage projects, guide junior consultants, conduct performance evaluations, and develop actionable insights for DHS.

The Sr. Data Architect II leads the design of secure data architectures for enterprise security platforms, ensuring compliance and integrating data solutions across hybrid environments while collaborating with cybersecurity teams.

The Data Engineer role involves developing and maintaining data pipelines for forecasting in commercial real estate, ensuring data integrity and supporting analytics teams.

Lead and deliver complex marketing analytics and predictive modeling projects. Own engagement delivery, synthesize analyses into strategic recommendations, manage timelines and teams, mentor junior staff, and support business development through thought leadership. Execute hands-on analysis using tools like Excel, R, SQL, Python, and SAS while maintaining client relationships and driving actionable sales and marketing improvements.

Design, build, and deploy scalable data pipelines and validation for government production environments. Establish and maintain schemas, optimize SQL, handle messy/disparate data sources, work with large (100GB+) workflows, use Databricks/Spark/Python, and support ML/predictive solutions while mentoring teammates and engaging with clients. Active Secret Clearance required.

The EV Data Analysis Lead will oversee data analysis projects, manage a team of analysts, and develop strategies to enhance transportation data services.

The Head of Data Science - Fraud Insights will lead research on fraud analytics, design predictive studies, manage a team, and communicate findings to influence strategy and policy.

Design and manage enterprise data architecture, including data modeling, database and storage solutions, governance, metadata, integration tooling, and mentoring data teams to support analytics and operations.

Lead fraud detection and mitigation for a conversational BNPL product. Define fraud typologies, own repayment and chargeback analytics, manage fraud KPIs, design operational policies, collaborate on ML models and decisioning workflows, and coordinate SARs and compliance reporting.