Top Analytics Jobs in Washington, DC

Lead data analysis for merchants, manage projects to improve product and acquisition strategies, and communicate insights effectively.

Leads medium- to large-scale analytics projects and client relationships while conducting data analysis, managing data infrastructure, building reports and calculators, and preparing client presentations. Provides strategic insights, oversees deadlines and quality, mentors analysts, collaborates with data science and technical teams, and communicates findings to technical and non-technical stakeholders.

Lead quantitative research and analytics for political and commercial clients: design experiments and surveys, manage RCTs and statistical modeling, generate strategic insights, oversee a team of data scientists and analysts, and deliver client-facing recommendations.

Data and Analytics Consultants help clients deliver strategic initiatives through data-driven decisions, requiring technical expertise and problem-solving skills.

Manage end-to-end polling operations, including questionnaire programming, sample selection, survey monitoring, data weighting, quality control, and client deliverables. Collaborate with project, data science, and polling teams on experiments, methodologies, and analytics surveys. Improve polling processes, coordinate vendors, analyze survey data under tight deadlines, and support strategic recommendations for clients.

Lead and grow customer analytics practice for Communications, Media & Technology clients. Define strategy, develop thought leadership, deliver large-scale analytics engagements, and drive CRM modeling, reporting, and predictive analytics initiatives.

The HR Data Analytics & Reporting Specialist analyzes HR data, develops reports and dashboards, collaborates with teams, and recommends operational improvements.

Responsible for analyzing HR data, developing reports and dashboards, identifying trends, collaborating with teams, and supporting operational efficiencies.

The Analytics/Dashboarding Analyst will design and implement analytics solutions, collaborate with teams, analyze challenges, and develop documentation to support operational efficiency.

The Analytics/Dashboarding Analyst will design and implement dashboards, analyze operational challenges, and develop documentation to support decision-making and efficiency improvements.

The Senior Analytics/Dashboarding Analyst designs dashboards, analyzes operational challenges, collaborates with teams, and enhances compliance and efficiency in mission-critical operations.

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.

Support product, content, and revenue teams by building and maintaining dashboards, performing ad hoc analyses of user engagement and monetization, validating data quality, and analyzing A/B test results to translate findings into clear insights that inform product and business decisions.

Perform data analysis and management, build reports, dashboards, calculators, and maps; present findings to clients and stakeholders; mentor junior staff; collaborate with data science and technical teams; use SQL, Python, GIS, BI and spreadsheet tools to translate data into actionable insights and client-facing deliverables.

The Data Engineer will develop data and software solutions for law enforcement, create reports, and manage data sources. Responsibilities include collaborating with teams to analyze data, communicate with clients, and ensure high-performance analytics tools.

This position involves supporting client-based data analytics and engineering projects, utilizing SQL, Python, or R, and presenting findings clearly.

The Data Analytics SME will assess technical practices, perform data analysis, and manage data cleansing for compliance and reporting purposes. Responsibilities include using Tableau, PowerBI, and SAS for analytics and reporting, as well as supporting cross-agency data initiatives.

Lead design and execution of the internal analytics stack: scale the data warehouse, build dbt ETL pipelines, model data for cross-functional reporting, create dashboards and forecasts, implement data quality checks, and partner with Product, Sales, Finance, and Operations to define KPIs and automate analytics workflows.