Top Data & Analytics Jobs in Washington DC,

Lead design, governance, and implementation of enterprise data and AI architectures. Define standards, mentor engineers, review projects, document target-state architectures, and drive adoption of scalable cloud data solutions.

Develop and maintain Tableau dashboards and visualizations from firm deal data, ensure data quality and validation, analyze deal terms for market insights, create customized reports for practice groups, support data-driven initiatives, and promote analytics adoption through training and collaboration.

The Digital Research Associate conducts digital and social media analysis, synthesizing data for client strategies using AI tools and collaborating with internal teams.

The Senior Analyst will lead empirical research and analytics, design datasets, present insights to clients, and collaborate across teams in healthcare analytics.

The Analytics Manager will lead analytics for the Payments and Identity lifecycle, manage a team of analysts, develop KPIs, and ensure data quality while collaborating with cross-functional teams.

The Data Analyst will build data pipelines, analyze complex datasets, and provide insights to support decision-making across multiple stakeholders in GFiber.

The Actuarial Analyst will conduct analyses for insurance pricing, support commercial auto pricing, and collaborate with cross-functional teams while mentoring junior staff.

Provide pre-sales technical leadership for field sales: design and validate data management and analytics solutions, lead POCs/demos, perform systems integration, and advise on cloud data platforms, unstructured data processing, RAG/GenAI, ETL/ELT, governance, BI and ML workflows.

Partner with customers and sales to design and present scalable Databricks Lakehouse architectures, build reference architectures and demos, consult on big data, ETL, and ML projects, validate integrations, and drive technical wins and adoption across accounts.

The role involves improving reserving models, developing predictive models using telematics and claims data, and influencing pricing and underwriting decisions through data analysis.