Top Senior Data Science Jobs in Washington, DC

Design and implement AI systems and scalable machine learning models, perform data wrangling and software engineering to deploy AI solutions, interpret data for client recommendations, collaborate across teams, uphold technical standards, and build client relationships while navigating complex, ambiguous problems.

Lead teams applying advanced data science and machine learning to large-scale claims, clinical, and member data to generate actionable insights that reduce cost of care and improve population health. Manage client relationships, mentor staff, ensure project delivery and quality, develop payer-focused analytics products, present findings to senior stakeholders, and promote continuous improvement and knowledge sharing.

Lead client-facing data science projects: develop and deploy ML/AI models, perform big-data analysis, feature engineering, predictive modeling, geospatial/signal/time-series analysis, mentor teammates, and translate data insights into actionable recommendations. Work often involves cloud environments and requires security clearance.

As a Senior Data Scientist, you will analyze complex datasets, develop algorithms, and provide insights to clients using machine learning and statistical methods. You'll lead projects, collaborate with teams, and apply data visualization to solve global challenges.

Design and implement ML and predictive analytics solutions on multi-INT datasets. Retrieve, merge, and analyze structured and unstructured data, build AI/ML tools, and produce visual and written analytic products for defense customers. Support database administration, data engineering, and deliverables in a classified, mission-driven environment.

Design and implement data pipelines and predictive models using SAP and non‑SAP data. Clean and validate large ERP datasets, perform statistical and exploratory analyses, build ML/AI solutions (SAP Analytics Cloud or external platforms), and produce dashboards and KPIs. Collaborate with IT and stakeholders to deploy data‑driven solutions and justify model value.

The Senior Database Architect analyzes and designs data solutions for enterprise reporting and operational decision-making, collaborating with various technical teams.

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.

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.

Develop and validate machine learning and advanced analytics solutions: prepare data, engineer features, train and evaluate models, integrate outputs into dashboards or workflows, collaborate with stakeholders, and communicate results to technical and non-technical audiences.

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.

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.

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.

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.

Lead development and delivery of predictive models and analytics for national security. Perform data collection, feature engineering, EDA, supervised/unsupervised modeling, entity resolution, text analytics, and operationalize production-ready decision-support tools while briefing stakeholders.

Lead design and execution of claims-based RWE and HEOR analyses using Medicare/Medicaid/commercial data. Develop and validate SAS programs, build reproducible analytic pipelines, synthesize findings for payer strategy and policy, mentor junior staff, and support client-ready deliverables and proposals.

Lead end-to-end data science work: exploratory and statistical analysis, data engineering, ML model development (recommendation engines, predictive systems), data visualization (Power BI, Tableau), and multi-int large-data analytics to support defense programs and produce actionable intelligence products.

Activate and operationalize clinical data for analytics by designing data models, taxonomies, and a clinical feature store; build reusable data assets, documentation, and dashboards; ensure data quality and compliance; partner with stakeholders and data engineering to enable downstream analysts, data scientists, and business users.