Top Data Science Jobs in Washington, DC

Leads teams in designing and deploying scalable AI and machine learning solutions for consulting clients. Responsibilities include data wrangling, complex analysis, data modeling, AI system implementation, data pipeline and infrastructure oversight, deep learning, neural networks, data quality validation, and stakeholder collaboration. The manager coaches team members, manages performance, supports innovation, and applies Python, Java, and cloud technologies to build production-ready AI applications.

Leads the design, development, and deployment of scalable AI, generative AI, and machine learning solutions. Oversees data infrastructure, integration, data quality, and advanced analytics while managing client engagements and executive relationships. Drives business development, strategic direction, innovation, and AI-driven automation. Mentors teams, develops future leaders, and fosters collaboration, integrity, and client satisfaction across complex projects.

Uses data exploration, cleaning, analysis, visualization, statistical programming, and machine learning to develop algorithms, predictive models, and quantitative insights from structured and unstructured data. Collaborates with clients to solve complex problems and advise decision-making across public and private sector applications. Requires a bachelor's degree and ability to obtain a Secret clearance.

Develop and strengthen client data science capabilities by analyzing complex structured and unstructured datasets, applying statistics and machine learning, evaluating AI/ML models, and translating findings into actionable insights. Collaborate with clients, mentor teammates, support defense and intelligence customers, and contribute to GEOINT, LLM, and all-source analysis efforts.

Develop algorithms, evaluate AI and machine learning models, and analyze complex structured and unstructured datasets to provide objective insights for clients. Collaborate with teams and stakeholders to understand business and intelligence questions, transform disparate data into actionable information, and support data analytics, visualization, AI governance, and intelligence-related initiatives. The role requires an active TS/SCI clearance and supports public-sector and national-security clients.

Leads the design, development, testing, and evaluation of AI and machine learning solutions. Directs data analysis, modeling, infrastructure, monitoring, and integration efforts while establishing standards for AI robustness, bias, explainability, failure modes, and technical controls. Manages large projects, advises clients, coaches teams, and develops reusable evaluation tools and evidence workflows for responsible AI deployment.

Designs, refactors, tests, and deploys secure PowerShell automation frameworks for Navy Records Management modernization. Processes large datasets, optimizes analytics pipelines, develops dashboards and workflow tools, and improves script performance, scalability, and resilience. The role applies Pester testing, secure coding, role-based access controls, Agile delivery, and data science practices while collaborating with program managers, developers, and Navy stakeholders.

Develop algorithms, systems, and analytical solutions that transform structured and unstructured data into actionable insights. Collaborate with clients and teams, evaluate AI and machine learning models, analyze complex datasets, and communicate findings that support informed decisions across government and private-sector challenges. The role may involve intelligence clients, AI governance, data visualization, and DoD analytical standards.

Supports DHS clients through data science consulting, including Power BI dashboard development, data cleaning with R and Python, analytics solution maintenance, reporting, and predictive analytics. The role balances ad hoc client requests with business development and internal initiatives, while communicating technical findings to nontechnical audiences. Candidates must hold a bachelor’s degree, use R or Python, and obtain and maintain a Federal or DHS Public Trust.

Develop advanced analytical models, predictive forecasts, and AI/ML capabilities supporting Navy Reserve readiness and mission assurance. Build analytics products, dashboards, and visualizations; apply statistical analysis, machine learning, data mining, and predictive modeling to identify risks and optimize resources. Collaborate with engineers, analysts, and government stakeholders, evaluate emerging technologies, communicate recommendations, and potentially lead analytic workstreams.

Designs and deploys advanced AI, machine learning, generative AI, and agentic solutions for fintech and payments. Responsibilities include owning the data science lifecycle, developing scalable ML pipelines, building RAG and foundation-model applications, applying AI to fraud, risk, forecasting, personalization, and payment optimization, and ensuring model governance, observability, privacy, and responsible AI practices. The role also mentors data scientists and partners with product, engineering, architecture, and business teams.

Leads payer healthcare data science and operations consulting initiatives, using business analytics to improve payer processes and performance. Manages teams, client relationships, project resources, strategic planning, process optimization, quality standards, and operational transformation. Coaches junior staff, promotes innovative technologies, and identifies opportunities to enhance operational excellence and business outcomes.

Analyze structured and unstructured data to identify insights and solve client problems. Develop predictive models, algorithms, quantitative analyses, visualizations, and data-processing systems using machine learning, artificial intelligence, and natural language processing. Collaborate with clients to understand analytical needs and translate complex datasets into objective, actionable information. The role requires TS/SCI clearance and supports applications across public and private sectors.

Develop predictive models, algorithms, and data-processing systems using structured and unstructured data. Perform data exploration, cleaning, analysis, visualization, mining, and quantitative modeling to help clients make informed decisions. Apply machine learning, artificial intelligence, NLP, and programming tools such as Python, R, and SQL across public- and private-sector challenges. Collaborate with clients and work with classified information under TS/SCI polygraph requirements.

Develops data science solutions supporting Army and Department of Defense platforms. Responsibilities include API integration, automated data pipelines, Palantir Foundry and Army Vantage development, data architecture, executive visualizations, statistical modeling, predictive machine learning, neural networks, and LLM customization. The role translates complex datasets into actionable insights for senior leaders and requires collaboration across technical and military stakeholders.

Develop and deploy predictive models, machine learning solutions, and advanced analytics for classified government intelligence missions. Analyze complex datasets, build ServiceNow-integrated data solutions, and create Tableau dashboards. Partner with government customers and engineering teams, ensure classified data compliance, and mentor junior staff. The role is fully onsite in Washington, DC and requires an active TS/SCI clearance with polygraph.

Analyzes complex, large-scale data to identify trends and organizational problems; applies statistical analysis, data mining, aggregation, and modeling techniques; prepares datasets, develops databases and data models, creates data-driven business solutions, and communicates findings to organizational stakeholders. Supports the Department of State’s Directorate of Passport Services.

Develops statistical analyses, predictive models, machine learning algorithms, and data visualizations from structured and unstructured data. Works with clients to identify data-driven solutions, query and transform relational data, guide teammates, and create systems that support informed decisions. The role requires collaboration in data-rich environments and may support intelligence, operations, fraud detection, or research applications.

Analyzes usage data across 15+ web applications, builds data pipelines, develops predictive models, and introduces AI/ML tools to improve analytics. Creates executive dashboards and reports, identifies trends and anomalies, communicates actionable recommendations, and ensures data integrity, security, and compliance. Collaborates with technical teams and business stakeholders while documenting analytical methodologies and presenting findings to leadership.

Develops algorithms, predictive models, quantitative analyses, and visualizations from structured and unstructured data. The role involves data exploration, cleaning, mining, and interpretation using statistical programming, machine learning, AI, NLP, and visualization tools. The data scientist collaborates with clients to address complex questions and translate disparate data into actionable insights for public- and private-sector challenges.

Analyzes structured and unstructured data using statistical methods, Python, machine learning, and artificial intelligence. Develops algorithms and systems, cleans and parses data, and translates complex datasets into actionable insights for clients across public and private sectors. Collaborates with clients and team members in fast-paced environments, including work involving intelligence processes and classified data.

Analyze disparate personnel datasets, develop Qlik or Tableau dashboards, create data manipulation scripts, identify trends, and translate findings into recommendations for senior leadership. The role also supports data management, enterprise analytics, AI products, secure handling of sensitive personnel information, data pipelines, technical writing, and business reporting. Required technologies include Databricks, Python, Spark, Pandas, SQL, and Qlik. An active Secret clearance and U.S. citizenship are required.

Develop data science algorithms, ETL pipelines, automated analytic software, statistical and machine learning models, and data visualizations. Collaborate with clients and teammates to interpret complex structured and unstructured data and deliver actionable insights. The role requires Python or R, version control, data engineering, visualization, and an active TS/SCI clearance with polygraph willingness. Preferred experience includes intelligence disciplines, deep learning, LLMs, distributed computing, and DevOps.

Leads data science initiatives by analyzing complex structured and unstructured datasets, developing ETL pipelines, predictive models, machine learning algorithms, and automated analytic software. Collaborates with clients, guides teammates, and translates data into actionable insights. Requires Python or R, statistical and machine learning expertise, version control, TS/SCI clearance with polygraph eligibility, and a bachelor's degree. Preferred experience includes intelligence disciplines, deep learning, LLMs, DevOps, data visualization, and ontology development.

Leads data science initiatives by analyzing complex structured and unstructured datasets, developing predictive models, machine learning algorithms, ETL pipelines, automated analytic software, and data visualizations. Partners with clients to define needs, translates data into actionable insights, guides teammates, and supports solutions involving AI, IoT, and intelligence analysis. Requires extensive programming, statistical modeling, data engineering, and classified-environment experience.