Top Data Science Jobs in Washington, DC

Analyze data to identify trends and anomalies, develop machine learning and statistical models, perform data parsing and ETL with Python and SQL, create dashboards, and collaborate with data engineers. The role emphasizes NLP, LLM, and Generative AI applications, quantitative analysis, model validation, and experimentation with emerging tools for federal clients.

Develops data pipelines, curates and analyzes large datasets, builds quantitative models, validates data and results, and deploys analytics solutions with product teams. Responsibilities include discovering useful datasets, ensuring data quality and reliability, supporting customer-driven requirements, and integrating solutions into interconnected systems. The role requires strong Python and data-handling skills, database expertise, large-scale batch processing experience, and U.S. citizenship.

Supports intelligence community projects through data acquisition, cleaning, statistical analysis, AI/ML model testing and evaluation, dashboards, visualizations, and reproducible documentation. Collaborates with senior staff and stakeholders to produce analytical outputs addressing defined business questions. The role requires an active TS/SCI clearance with CI polygraph and supports Department of Defense or Intelligence Community clients.

Supports intelligence community programs through data acquisition, preparation, statistical analysis, analytics, and testing and evaluation of AI/ML models. Builds reports, dashboards, and visualizations; documents reproducible methods and results; and presents findings to stakeholders. The role requires collaboration with federal defense and intelligence clients and an active TS/SCI clearance with CI polygraph.

Analyzes complex datasets using statistical methods, machine learning, and AI techniques. Builds and evaluates predictive models, develops reproducible analytical workflows, supports production deployment, and applies NLP, generative AI, LLMs, deep learning, and time-series methods. Partners with engineers and stakeholders to deliver mission-focused solutions, documents findings, and supports responsible AI practices including explainability, trustworthiness, and risk management.

Supports DHS clients through data science consulting, including dashboard and visualization development in Tableau, data cleaning with R and Python, analytics solution maintenance, reporting, predictive analytics, and ad hoc analysis. The role also involves client communication, business development support, and explaining technical concepts to nontechnical audiences.

Perform data science, engineering, analytics, and statistical work for Department of War and Intelligence Community clients. Test and evaluate AI/ML models, collaborate with teams, communicate findings, and support or conduct all-source analysis. Experience with GEOINT and large language models is preferred. The role requires an active TS/SCI clearance and ability to pass a CI polygraph.

Conduct data science, engineering, and analytics work supporting Department of War and Intelligence Community clients. Test and evaluate AI/ML models, potentially work with large language models, perform all-source analysis, and collaborate with multidisciplinary teams. The role requires an active TS/SCI clearance with a recent CI polygraph and a bachelor’s degree or equivalent direct experience.

Develops and evaluates data science and AI/ML models while supporting Department of War and Intelligence Community clients. The role requires collaborating across teams, communicating effectively, conducting testing and evaluation, and potentially applying large language models and all-source analysis. Candidates must hold an active TS/SCI clearance with a current CI polygraph and have a bachelor’s degree or at least four years of direct data science experience.

Analyzes structured and unstructured financial and ERP data using Python, SAS, statistical methods, predictive modeling, and advanced algorithms. Supports Oracle E-Business Suite financial processes, data conversion, reporting, and continuity of operations planning. Develops models and actionable insights for business decisions, collaborates with engineering and disaster recovery teams, maintains contingency plans, and executes recovery exercises. Requires a master’s degree, 5+ years of experience, Oracle expertise, certification eligibility, and approximately 25% annual travel to Washington, DC.

Analyze large customer datasets, evaluate machine-learning models, develop risk and fraud insights, and communicate data-driven recommendations to technical and nontechnical audiences. The role partners with sales and account teams throughout pre- and post-sales, creates automated analytical workflows, supports product optimization and upsell opportunities, and may build exploratory ML models. It also contributes thought leadership on identity verification, fraud prevention, model performance, and customer risk management.

Perform data exploration, cleaning, analysis, and visualization; develop predictive models and algorithms on structured and unstructured data; apply ML/AI/NLP techniques to deliver client-facing solutions. TS/SCI clearance required.

Build and validate analytical models using large structured datasets to improve operational and business outcomes. Translate complex findings into actionable recommendations, partner with engineering, design, and product teams to deploy production-ready solutions, lead high-impact federal projects, mentor junior staff, and shape data science strategy for Department of Education programs.

Designs, develops, and operationalizes machine learning models and advanced analytics for a 24x7 Security Operations Center. Analyzes security telemetry, builds data pipelines and feature engineering workflows, integrates analytics with SOC tools using Docker and Kubernetes, and applies threat frameworks such as MITRE ATT&CK. Provides technical leadership, mentors analytics personnel, collaborates with SOC analysts and engineers, and delivers documentation, performance metrics, and leadership briefings.

Builds dashboards, applications, automations, ETL integrations, predictive risk models, and AI/ML solutions for unstructured data. Performs data normalization, visualization, business intelligence analysis, and risk assessment improvement. Recommends data storage and integration solutions, creates Power BI documentation, and applies SQL, R, Python, and other data science tools to federal systems and public-sector projects.

Develop and maintain credit risk models for origination, behavioral risk, underwriting, and portfolio management across Latin America. Own the full modeling lifecycle, including feature engineering, validation, backtesting, monitoring, calibration, and implementation. Analyze large financial datasets using Python and SQL, monitor portfolio and model performance, address data quality and selection bias, and translate analytical findings into credit strategies. Collaborate with Risk, Data, Engineering, Finance, and Operations teams.

Develops and enables clinical data assets for analytics and AI/ML across healthcare use cases. Responsibilities include designing clinical data models, taxonomies, feature stores, documentation, quality frameworks, dashboards, and reusable datasets. The role partners with clinical, business, and engineering stakeholders, supports data governance and HIPAA compliance, translates clinical concepts into analytical frameworks, and trains downstream data consumers. Expertise in clinical coding systems, healthcare datasets, SQL, cloud platforms, and clinical informatics standards is required.

Develop and deploy complex machine learning and analytics models for client systems. Manage large datasets, perform data ingestion, cleaning, feature extraction, modeling, validation, visualization, and reporting. Collaborate with clients and distributed data science and systems engineering teams while delivering maintainable, tested, version-controlled, cloud-based solutions within cost and schedule constraints.

Develops data-driven solutions for government and strategic customers by acquiring and preparing datasets, evaluating and improving statistical models, building scalable operational models, researching industry trends, and collaborating with software engineers, technical program managers, designers, and customers on cloud-based AI projects.

Lead data science, data engineering, and applied AI as the program’s senior technical authority supporting DIA analysts. Establish responsible and auditable AI standards, guide analytic tools from pilot through deployment in classified environments, mentor technical staff, develop training, coordinate with government and partner teams, support hiring, and remain hands-on in data science and tool development.

Leads data science engineering projects with government and strategic customers, overseeing data acquisition, preparation, modeling, evaluation, ethics, privacy, and scalable operational models. Coaches engineers, develops extensible code, researches industry trends, identifies strategic opportunities, and delivers customer-focused AI and cloud solutions. Requires advanced education or equivalent experience, extensive data science experience, active TS/SCI clearance with polygraph eligibility, U.S. citizenship, and Microsoft background screening.

The Data Scientist will support Army network and enterprise information environment missions by analyzing complex datasets, developing statistical and machine learning models, integrating APIs and automated data pipelines, and building Palantir Foundry and Army Vantage applications. The role includes creating executive visualizations, applying AIP tools, supporting secure Army and DoD data environments, and translating technical findings into actionable recommendations for senior leadership.

Analyze complex structured and unstructured datasets to answer client questions, evaluate AI and machine learning models, and deliver objective insights for leadership decisions. Collaborate with clients and teammates, mentor colleagues, and strengthen data science capabilities supporting Department of War or Intelligence Community clients. The role may involve GEOINT, LLMs, and all-source analysis in a classified environment.

Lead development and deployment of machine learning models, provide technical leadership on AI/ML solutions, integrate models with data pipelines, build RPA automations, support data governance, evaluate analytics products, and present findings through dashboards and reports to stakeholders.

Provides data science consulting support to DHS by developing Power BI dashboards, cleaning and transforming data with Python and R, maintaining analytics solutions, and delivering predictive analytics and business intelligence. The role involves client communication, ad hoc analysis, requirements gathering, business development support, and translating technical topics for nontechnical audiences. Familiarity with cloud analytics platforms, PowerApps, ETL/ELT, financial data, and workload modeling is beneficial.