Top Data Science Jobs in Washington, DC

This role involves applying advanced data science and machine learning methods to healthcare data, leading teams, managing client relations, and developing analytics products for payers, while mentoring junior staff.

Perform data exploration, cleaning, analysis, and visualization; develop predictive models and algorithms using ML/AI/NLP techniques; collaborate with clients to translate data into actionable insights and deploy analytical solutions.

Use analytics, machine learning, and AI to explore, clean, and analyze structured and unstructured data. Develop predictive models, algorithms, and visualizations to answer client questions across public and private sectors. Work closely with clients to translate problems into data solutions and apply appropriate tools and frameworks to deliver actionable insights.

Apply advanced analytics, statistical modeling, and machine learning to intelligence data. Develop predictive models, perform exploratory analysis on structured and unstructured data, collaborate with analysts and mission partners, and present findings via visualizations and reports using Python or R and common data science tools.

Lead design, build, and production deployment of generative AI products (LLM apps, agents, copilots, RAG/search). Rapidly prototype features, build APIs/services and retrieval pipelines, optimize performance, ensure responsible AI, and mentor team members while setting AI technical direction across the organization.

Collect, integrate, and prepare data from multiple sources; design data models, predictive algorithms, and ML solutions; build dashboards and visualizations; ensure data quality and support analytics for FBI financial management, client delivery, and business development.

The Data Scientist III will enhance cybersecurity operations using data science and machine learning techniques, developing analytical models, and integrating data from various sources to improve threat detection and monitoring.

As a Data Scientist focused on policy, you'll analyze data to inform policy discussions, support partnerships, and measure impact on public perception. You'll collaborate cross-functionally to create clear evidence and frameworks for AI policy communications.

Support Defense Intelligence analysts by building data pipelines, ML models, and analytics for multi‑INT data. Perform data engineering, mining, predictive analysis, and deliver visualizations. Use Python, R, SQL, Power BI, and Tableau. Work requires active TS/SCI clearance and 8+ years of data science experience.

Lead and architect enterprise-scale multi-INT data science solutions: build and deploy ML models, pipelines, and recommendation systems; advise customers on data constraints; review models and code for rigor; mentor and technically lead mid-level data scientists; evangelize reproducible best practices.

Perform quantitative real estate and urban economic analysis, applying econometric and spatial methods to synthesize property, macroeconomic, and geospatial data. Build and maintain automated data pipelines, ensure data integrity, document dataflows, and prototype ML/AI methods. Collaborate with research, GIS, and engineering teams to produce reproducible insights and analytical products for stakeholders.

Join AIS supporting a federal client in the DMV to develop, train, and deploy AI/ML models from ideation to production. Use Python and common data-science libraries, work with database systems, collaborate on hybrid teams, and meet security clearance requirements.

Develop and lead data science solutions: build ETL pipelines, clean and model structured/unstructured data, design algorithms and automated analytics, produce visualizations, use ML methods, collaborate with clients and mentor teammates to turn data into actionable insights for government and commercial problems.

Work with clients to formulate questions, explore and clean structured and unstructured data, build predictive models and algorithms, develop automated analytic software and ETL pipelines, and create visualizations and insights to support decision-making in intelligence and commercial contexts.

Support federal client engagements by preprocessing and engineering NLP features, building and validating classification and deep-learning models (transformers), and presenting model results and visualizations to inform public-sector decisions. Work includes production-ready NLP development, model validation, and collaboration on user stories.

Build and deploy credit risk models for acquisition and account management. Create datasets and features from traditional and non-traditional sources, collaborate with credit, product, and engineering partners, run experiments, and monitor models in production to enable responsible lending decisions.

The role involves using data science skills to extract insights from data, develop algorithms, and create analytics solutions for clients across various sectors, particularly in fraud detection, cancer research, and national intelligence.

As a Senior Data Scientist, you'll analyze complex data to provide insights, develop algorithms, and lead teams to address clients' questions using machine learning and predictive modeling methods.

Lead development of production-grade fraud and identity risk signals from high-scale device, network, browser, mobile, API, and behavioral telemetry. Define evaluation methods, build scalable feature engineering, investigate adversarial signal patterns, influence telemetry and production readiness, mentor data scientists, and drive technical direction for robust, explainable, low-latency decisioning systems.

Develop ML features, models, and analytical methods from device, network, browser, mobile, session, and behavioral telemetry to detect fraud and improve identity confidence. Handle large-scale, noisy, high-cardinality data, design validations, assess drift and leakage, collaborate with engineering/product/risk for production rollout, document models and features, and mentor junior team members.

Work with clients to translate data into actionable insights using machine learning, AI, and IoT data. Lead development of algorithms, automated analytic software, ETL pipelines, and data visualizations; integrate FOSS/COTS and support model deployment. Must hold TS/SCI clearance.

Design and implement data science solutions: ingest and clean data, build ETL pipelines, develop predictive models and algorithms, create visualizations, lead teammates, and deliver analytic products for intelligence and commercial clients while maintaining classified clearance requirements.

Work with clients to analyze large, structured and unstructured data sets, build ETL pipelines, develop machine learning models and automated analytic software, produce visualizations, guide teammates, and translate insights into actionable recommendations for public- and private-sector problems.

Provide advanced data science and analytics to support audits, inspections, evaluations, and investigations for a U.S. government agency. Tasks include data acquisition, cleaning, entity resolution, statistical and fraud-risk analysis, dashboard and visualization development, investigative link and timeline analysis, reporting for audits and prosecutions, and supporting data governance, reproducibility, and training for government personnel.

Lead data science engagements: work with clients to define problems, build ETL pipelines, develop machine learning models and algorithms, create visualizations, guide teammates, and deploy analytic solutions to inform decision-making across classified and unclassified environments.