Top Data Science Jobs in Washington, DC

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.

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.

Design and deploy AI systems and machine learning models, perform data wrangling and analysis, and integrate solutions into data infrastructure. Develop scalable AI applications, relational data systems, evaluation tools, automated tests, and monitoring capabilities. Assess AI behavior, robustness, bias, explainability, drift, hallucinations, and guardrails while evaluating technical controls and communicating findings to clients and stakeholders.

Develop and implement AI and machine learning solutions, including algorithms, data models, infrastructure, evaluation tools, automated tests, monitoring, and responsible AI controls. Lead testing for robustness, bias, drift, explainability, hallucinations, and failure modes. Manage client accounts and technical workstreams, review evidence and controls, communicate trade-offs, mentor teams, and maintain delivery and professional standards.

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.

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.

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.

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.

Develops and deploys production machine learning models and data science solutions for business, legal, investigative, and regulatory needs. Designs AI evaluation frameworks assessing bias, accuracy, reliability, and performance; analyzes structured and unstructured data; builds pipelines and testing tools; and translates legal and business requirements into technical solutions. The role collaborates with lawyers, clients, and cross-functional teams, manages concurrent engagements, communicates insights, and supports revenue-generating professional-services delivery.

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.

Develop data science algorithms, analytic software, ETL pipelines, and predictive models from structured and unstructured data. Collaborate with clients to identify needs, analyze complex datasets, and deliver objective insights for decision-making. Guide teammates and support applications across areas such as fraud detection, cancer research, and national intelligence. The role requires TS/SCI clearance and may involve intelligence data disciplines, DevOps practices, and data visualization.

Develops algorithms, predictive models, quantitative analyses, and visualizations from structured and unstructured data. Collaborates with clients to understand analytical needs, explores and cleans data, applies machine learning, AI, NLP, and text-mining techniques, and translates complex datasets into actionable insights for informed decision-making across public and private sector challenges.

Develop data science algorithms, analytic software, ETL pipelines, and predictive models using structured and unstructured data. Partner with clients to understand analytical needs, create data visualizations, integrate software solutions, and guide teammates. The role requires experience with Python or R, statistical and machine learning methods, version control, and data engineering workflows. Work may support intelligence and operations analysis and requires TS/SCI clearance.

Designs and deploys machine learning models, statistical analyses, data workflows, and custom algorithms for law enforcement, intelligence, investigative, and business datasets. Collects, cleans, processes, and analyzes large datasets; validates data quality and model performance; deploys predictive models; and presents actionable recommendations through visualizations to government stakeholders and executive leadership.

Executive-level Data Scientist serving as principal technical authority for machine learning, statistical analysis, data engineering, and predictive modeling across law enforcement, intelligence, and investigative datasets. Designs algorithms, data pipelines, quality frameworks, enterprise search solutions, and visualizations; collaborates with senior government stakeholders and multidisciplinary teams; and delivers actionable recommendations and briefings to executive leadership. Requires extensive experience with large-scale structured and unstructured data and an active Top Secret/SCI clearance with CI Polygraph.

Develop predictive models, algorithms, quantitative analyses, and visualizations from structured and unstructured data. Collaborate with clients to understand data needs, lead solution development, apply machine learning and NLP techniques, and translate complex information into actionable insights. The role also involves guiding teammates and advising clients across public and private sector challenges.

Model CBRN and nuclear effects across operational environments, analyze hazard and toxicity data, automate large-scale modeling runs, and develop tools that transform raw modeling and observational data into tables, graphics, and actionable technical assessments. The role supports Air Force CWMD operations, technical research, operational evaluations, and advising operators on CBRN defense threats and test results.

Develop algorithms and data systems to analyze structured and unstructured data, apply statistical and scientific methods, and generate objective insights for clients. The role requires programming in R or Python, data interpretation, and collaboration in a fast-paced environment. Preferred experience includes data cleansing, parsing, intelligence processes, development tools, and Windows and Linux environments. The position is onsite and requires TS/SCI clearance with a polygraph.

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.

Analyze federal workforce data and position descriptions using statistical modeling, NLP, machine learning, and text analytics. Develop dashboards, visualizations, and reports; map duties and skills to job series and grade levels; validate findings with HR professionals and leadership; and provide recommendations supporting accurate, compliant job classification and reclassification decisions.

Design and maintain scalable data pipelines and analytical workflows using Databricks, Python, Spark, and SQL. Automate ingestion, transformation, reconciliation, and delivery across structured and semi-structured datasets. Implement data-quality controls, validation, schema enforcement, anomaly detection, and integrity checks. Troubleshoot ETL failures, improve processing efficiency, collaborate with mission stakeholders, and develop dashboards, models, and decision-support products for financial reporting and enterprise analytics.

Develop algorithms, predictive models, quantitative analyses, and visualizations from structured and unstructured data. Apply Python and statistical programming to data exploration, cleaning, mining, and analysis while using machine learning, AI, and NLP techniques. Collaborate with clients to translate data into actionable insights and support informed decisions across public and private-sector challenges.