Top Data Science Jobs in Washington, DC

As a Senior Associate in the Financial Crime Unit at PwC, you'll analyze complex datasets using SQL and Python, apply machine learning techniques, mentor junior team members, and build client relationships while enhancing your technical skills.

Lead product analytics for in-vehicle experiences: define KPIs and instrumentation, perform deep-dive behavioral analyses, build dashboards and self-serve analytics, guide experimentation and causal inference, and mentor teams to scale analytics practices across the Vehicle Product organization.

This role involves applying advanced data science and machine learning methods to healthcare data, leading teams, managing client relations, and developing analytics products for payers, while mentoring junior staff.

The Mid level Data Scientist will build and improve dashboards, develop predictive models, extract insights using AI/ML, and enhance BI tools while supporting impactful projects.

As a Mid Data Scientist, you'll leverage data science techniques and tools to analyze data sets, create algorithms, and provide actionable insights for clients in various sectors, including health and national security.

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.

Data Scientists at BlueLabs build predictive models, collaborate on analytics products, and tackle complex data challenges while ensuring high data quality.

Provide data science and BI expertise to modernize federal financial management: build dashboards and automated reports, analyze large financial datasets, support audit readiness and reconciliation, develop data models and governance, and present findings to leadership to improve reporting, controls, and decision-making.

Lead data-science and risk-analytics for risk-based review selection. Build, maintain, and operate models, scripts, formulas, and dashboards that rank partner agencies by risk. Aggregate and validate data, compute health scores, visualize findings and trends, support quarterly risk meetings, and maintain the Risk Support Work Plan.

As a data scientist, you will analyze complex datasets, develop algorithms, and provide insights for decision-making in various sectors. You will lead teams, mentor colleagues, and utilize tools to create data-driven solutions.

As a Data Scientist, you will design and develop data pipelines, perform data analysis, and collaborate with the product team to implement solutions for large datasets.

The Data Scientist will design and deploy AI-driven data solutions, managing data pipelines and machine learning services in secure environments for the Department of Defense.

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.

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.

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.

Perform claims-based HEOR and RWE analyses using Medicare and Medicaid data, design and execute analytic studies, produce Excel and PowerPoint deliverables, communicate results to stakeholders, manage data analysts, and assist with QA of programs and analyses to inform market access and policy decisions.

Perform quantitative real estate and urban economic analysis, applying econometric and spatial methods to synthesize property, macroeconomic, and geospatial data. Build and maintain automated data pipelines, ensure data integrity, document dataflows, and prototype ML/AI methods. Collaborate with research, GIS, and engineering teams to produce reproducible insights and analytical products for stakeholders.

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.

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.

As a Senior Data Scientist, you will leverage programming languages and analytical techniques to transform complex datasets into actionable insights, guiding clients in decision-making.

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.

Support federal client engagements by preprocessing and engineering NLP features, building and validating classification and deep-learning models (transformers), and presenting model results and visualizations to inform public-sector decisions. Work includes production-ready NLP development, model validation, and collaboration on user stories.

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.

Work with clients to formulate questions, explore and clean structured and unstructured data, build predictive models and algorithms, develop automated analytic software and ETL pipelines, and create visualizations and insights to support decision-making in intelligence and commercial contexts.