Top Senior Data Science Jobs in Washington, DC

Designs and optimizes AI and machine learning solutions, transforms data into insights, and develops production AI systems. Responsibilities include building data infrastructure, speech recognition and NLP tools, and reusable evaluation and monitoring capabilities. The role independently tests AI systems for performance, robustness, bias, explainability, and failure modes; evaluates technical controls; documents findings; communicates recommendations to clients; and mentors junior team members.

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.

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.

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.

Perform advanced data science for Army NC4SI: develop ML models (ensembles, neural nets, LLM vectorization), design/optimize Army Vantage environments, integrate and deploy APIs and automated data pipelines across Army/DOD platforms, analyze complex datasets, ensure data architecture, security, and compliance in DOD cloud environments, and collaborate with military and technical teams.

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.

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.

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.

Develops advanced data analysis, visualization methodologies, intelligence support packages, and machine learning models for a federal client. Processes disparate data, identifies trends and relationships, delivers infographics and stakeholder briefings, documents technical solutions, and supports architectural reviews. The role requires Python-based data science experience, Agile development familiarity, strong communication skills, a bachelor’s degree, and an active Top Secret/SCI clearance.

Develop and evaluate supervised and unsupervised machine learning and AI models for a federal law enforcement data program. Apply NLP to extract and enrich entities from unstructured data, prepare structured and unstructured datasets, create visualizations, and communicate findings to technical and non-technical stakeholders. Collaborate with an Agile delivery team on enterprise data analytics and mission-focused modeling.

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.

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.

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.

Conducts data analytics, engineering, mining, statistical analysis, predictive modeling, and intelligence-focused data visualization. Designs and optimizes data architectures, storage, access, integration, throughput, and query performance. Builds AI automation tools and prediction systems from disparate data sources, collaborates with intelligence community members, communicates complex findings, and develops concise defense intelligence products. Requires active TS/SCI clearance, U.S. citizenship, and ability to obtain a counterintelligence polygraph.

Develop and deploy machine learning models and statistical algorithms to detect financial crime using large-scale BSA/AML transaction data. Perform exploratory analysis, feature engineering, validation, SQL analysis, visualization, and documentation using Python, R, PySpark, AWS, and related tools. Collaborate with investigators, compliance analysts, and technical stakeholders to translate regulatory requirements into analytical solutions. The role requires active Top Secret clearance with SCI eligibility and full-time onsite work in Washington, DC.

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.

Seeking a Data Scientist with 5+ years experience to develop and fine-tune AI/ML solutions, focusing on large language models. Collaborate with engineering teams to deploy robust models in production while applying modern techniques.

The Data Scientist/Analyst will evaluate economic performances, develop performance metrics, and create dashboards for the Department of State, while collaborating on complex challenges through data-driven insights.

Own product analytics across Axon’s ecosystem, partnering with product managers to define metrics, validate tracking, build durable data models, and deliver decision-focused analyses. Apply segmentation, experimentation, forecasting, and causal inference to product adoption and engagement questions. Help establish shared metric and reporting standards, maintain data quality and documentation, and explore AI agents for querying, anomaly detection, and insight generation.

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.