Top Data Science Jobs

Performs data science for a Joint Interagency Task Force supporting counter-UAS capabilities. Develops data taxonomies, analyzes data trends, provides data modeling for algorithms, and creates data-sharing mechanisms with external stakeholders. The role requires systems and cloud administration expertise, preferably with Microsoft Azure Government and Palantir Foundry, and involves onsite work in Alexandria, Virginia with occasional field travel.

Develops predictive models and transforms structured and unstructured data into actionable insights. Responsibilities include data wrangling, statistical analysis, machine learning, visualization, reporting, data pipeline management, cloud and DevSecOps integration, root-cause analysis, and technical solution development. The role supports government stakeholders, guides junior personnel, leads data projects independently, validates AI models, documents algorithms, and communicates findings through briefings and presentations.

Leads advanced data science and machine learning initiatives for healthcare payment integrity, including fraud, waste, and abuse detection, anomaly identification, predictive modeling, statistical analysis, dashboards, and recovery investigations. Provides technical leadership, mentors analysts, integrates production analytical solutions, collaborates with legal and business stakeholders, and presents findings to leadership. Requires healthcare expertise, advanced SQL and programming skills, and knowledge of claims, billing, reimbursement, and program integrity.

Analyze data to identify trends and anomalies, develop machine learning and statistical models, perform data parsing and ETL with Python and SQL, create dashboards, and collaborate with data engineers. The role emphasizes NLP, LLM, and Generative AI applications, quantitative analysis, model validation, and experimentation with emerging tools for federal clients.

Develop audience segments, customer profiles, and predictive models using behavioral, transactional, viewing, and digital data. Apply statistical and machine learning methods for clustering, churn, propensity, content affinity, and customer value analysis. Conduct exploratory analysis, evaluate models, support campaign measurement, and translate findings into business recommendations. Collaborate with Marketing, Product, Media Sales, and Content teams while presenting insights to technical and non-technical stakeholders.

Administers UMM data-management infrastructure, including access controls, configuration, dashboards, data flows, ingestion validation, monitoring, and security compliance. Provides advanced tier-two technical support, troubleshoots issues, supports testing and user acceptance, documents configurations, and coordinates enhancements with engineering and data stakeholders. The role supports distributed DoD and Intelligence Community users and requires on-site work in a DIA SCIF with an active TS/SCI CI Poly clearance.

Develops standardized performance methodologies and analytical products using intelligence and operational data. The role identifies trends, anomalies, risks, and optimization opportunities; creates KPIs, scorecards, dashboards, reports, and executive briefings; and supports resource allocation, operational planning, collection management, and leadership decisions. Responsibilities include data validation, cleansing recommendations, documentation of analytical methods and limitations, and coordination with operational stakeholders, engineers, administrators, and leadership.

Develops and evaluates AI and machine-learning models for intelligence collection prioritization, tasking automation, resource optimization, and mission planning. Responsibilities include data preparation, predictive modeling, validation, monitoring, explainability, responsible AI, and collaboration with software engineers on deployment. The role briefs technical and mission stakeholders and requires work in a DIA SCIF supporting secure DoD and Intelligence Community operations.

Own data science for payment performance, optimization, timing, retry strategies, monitoring, experimentation, and fraud detection. Build payment-health scorecards, anomaly monitoring, payment-risk models, and production ML systems using Python, SQL, PySpark, Databricks, and MLOps tooling. Partner with Engineering, Product, and Risk to shape payment strategy and roadmap while applying causal inference, feature engineering, and production model monitoring.

Build Boulevard’s Product Intelligence function by developing product data foundations, pipelines, dashboards, experimentation practices, and customer behavior models. Partner with Product, Engineering, and leadership to deliver actionable insights, self-serve analytics, and productionized models. Establish scalable processes, instrumentation standards, statistical workflows, and data-driven decision-making across the organization.

Develops data pipelines, curates and analyzes large datasets, builds quantitative models, validates data and results, and deploys analytics solutions with product teams. Responsibilities include discovering useful datasets, ensuring data quality and reliability, supporting customer-driven requirements, and integrating solutions into interconnected systems. The role requires strong Python and data-handling skills, database expertise, large-scale batch processing experience, and U.S. citizenship.

Leads data science initiatives supporting USPACOM J7, including AI integration, predictive modeling, data pipeline architecture, governance, dashboard optimization, and large-scale data analysis. Collaborates with technical teams, leadership, and subject matter experts to deliver secure, scalable, mission-critical data solutions. Requires programming, statistical and machine learning expertise, cloud familiarity, containerized application experience, and an active Secret clearance with eligibility for TS/SCI.

Develop and productionize statistical and machine learning solutions for financial crime detection. Responsibilities include NLP, entity resolution, document classification, knowledge graphs, topic modeling, scalable ML pipelines, large-scale data analysis, and translating business challenges into quantitative problems. The role collaborates with Product, Platform Engineering, Sales, and clients, requiring clear communication with technical and non-technical audiences.

Develop statistical and machine learning models using soccer tracking and event data to support player recruitment decisions. Build spatio-temporal models, metrics, analyses, and interpretation tools; validate models; communicate findings to professional club clients; and partner with engineering on cloud deployment and production reliability. The role also includes code review, model maintenance, and advancing analytical methods.

Lead data science and marketing analytics initiatives that improve member activation, engagement, retention, and health outcomes. Develop segmentation, propensity, predictive, and prescriptive models; design experiments and A/B tests; establish measurement frameworks; and translate insights into campaign and product strategies. Partner with Product, Marketing, Care Management, Data Engineering, and MLOps teams to operationalize targeting models and scale personalized engagement programs.

Supports intelligence community projects through data acquisition, cleaning, statistical analysis, AI/ML model testing and evaluation, dashboards, visualizations, and reproducible documentation. Collaborates with senior staff and stakeholders to produce analytical outputs addressing defined business questions. The role requires an active TS/SCI clearance with CI polygraph and supports Department of Defense or Intelligence Community clients.

Supports intelligence community programs through data acquisition, preparation, statistical analysis, analytics, and testing and evaluation of AI/ML models. Builds reports, dashboards, and visualizations; documents reproducible methods and results; and presents findings to stakeholders. The role requires collaboration with federal defense and intelligence clients and an active TS/SCI clearance with CI polygraph.

Build geospatial data pipelines and predictive risk models using LiDAR, terrain, GIS, asset, and weather data. Develop physics-backed simulations for grid risks such as conductor sag, vegetation encroachment, wildfire ignition, and extreme-weather failures. Collaborate with utility GIS teams, establish spatial QA/QC standards, translate complex metrics into investment insights, integrate customer systems, and mentor others in data science and product development.

Develops and maintains data pipelines, analyzes structured and unstructured data, and applies statistics, machine learning, NLP, predictive modeling, and advanced analytics. The role includes data engineering, algorithm development, cloud-based ML platform use, visualization, experimentation, and communicating insights to nontechnical audiences. Candidates must hold a STEM bachelor’s degree, have 3–5 years of data science experience, programming proficiency, Agile and Git experience, and a TS/SCI clearance.

Develops NLP and machine learning solutions for VA disability claims, extracting and structuring medical and claims data. Builds and maintains NLP pipelines, tunes transformer models, validates accuracy, documents workflows, collaborates with VA stakeholders, and integrates models into government systems. Requires healthcare or claims data experience, cloud familiarity, and the ability to communicate technical concepts effectively.

Develop data science solutions for Navy mission applications by analyzing complex structured and unstructured data. Build algorithms, scripts, predictive analytics, statistical and simulation models, and machine learning solutions. Apply data engineering practices, statistical software, and natural language processing techniques to generate actionable insights that support military decision-making. Collaborate with customers to understand analytical needs and communicate findings.

Conduct quantitative analysis, process complex and geospatial data, develop visualizations, and create data-driven insights. Build Python-based data-cleaning and manipulation workflows while working with AI/ML technologies and multiple file formats. Desired work includes NLP document extraction, computer vision, automated collection and reporting, data standardization, and statistical techniques such as classification, regression, clustering, data reduction, and causal modeling.

Leads enterprise data science, AI, machine learning, and advanced analytics strategy supporting NASIC. Designs analytical architectures, optimizes complex data workflows, develops governance frameworks, evaluates cloud capabilities, and guides AI/ML deployment. Produces executive dashboards and progress reports, creates technical policies, and coordinates with data, AI, infrastructure, and intelligence stakeholders. The role requires extensive computational experience, DoD/IC standards expertise, cloud proficiency, and an active TS/SCI clearance.

Develops and deploys AI/ML and intelligent automation workflows for complex intelligence datasets. Builds statistical models, data pipelines, dashboards, and scalable software outputs within secure cloud infrastructure. Integrates data strategies with Zero Trust Architecture, supports reporting and technology prototyping, and collaborates with engineers, database administrators, and product owners. Requires active TS/SCI clearance and onsite support at Wright-Patterson AFB.

Develops automated collection models, analytic models, workflow automations, and data-processing solutions supporting intelligence strategies. Evaluates and improves automated solutions using performance data and stakeholder feedback. Applies data science, visual programming, geospatial tools, statistical methods, machine learning, and visualization to address intelligence integration, automated collection, information sharing, and analytic workflow challenges.