Top Remote Data & Analytics Jobs in Washington, DC

The Director of Data and Enterprise Applications oversees the architecture, development, and support of business applications and data platforms, driving digital transformation and ensuring data integrity and accessibility.

The Analytics Lead will guide data-driven decision-making, develop measurement frameworks, forecast revenue, and mentor an analytics team, ensuring effective communication of insights.

The Director of Business Intelligence at Viral Nation will lead analytics strategy for a CPG organization, driving insights and growth opportunities across sales, marketing, and digital engagement. Responsibilities include building a high-performing team, developing predictive models, and optimizing measurement strategies to inform executive decisions.

Design and scale data infrastructure, ensure data quality and governance, collaborate with teams on data products, and modernize practices.

The Senior Data Scientist will lead analytics efforts, develop data models, and improve data pipelines to support Thyme Care's mission in oncology care, while collaborating with stakeholders to enhance performance metrics and reporting.

Lead Oracle Cloud reporting initiatives, ensuring data accuracy and performance while mentoring junior analysts and collaborating with stakeholders.

Design and maintain data systems for business-critical insights, connect data across platforms, build ETLs, and support business data decisions.

Lead design and development of web UI and REST middleware within an Agile team. Define requirements and acceptance criteria, implement Java/Spring and Angular solutions, build CI/CD pipelines, work with Product Owner and testers, and produce/update design documentation.

Lead analytical efforts in Real World Data research, develop specifications and methodologies, manage projects, and communicate findings to stakeholders.

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 Data Engineer builds and maintains data infrastructure, develops data pipelines, ensures data quality, and collaborates with teams for insights.

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