Top Data Science Jobs

Develops predictive models, quantitative analyses, data visualizations, and machine learning solutions for Department of Defense clients. Responsibilities include data exploration, cleaning, mining, statistical programming, natural language processing, text mining, dashboard development, and advising stakeholders on actionable insights. Requires experience with Maven Smart System and a TS/SCI clearance.

Develop machine learning and advanced analytics models for sparse, noisy, and adversarial intelligence datasets. Translate analytic questions into technical requirements, assess data quality, recommend technical approaches, communicate findings to technical and non-technical stakeholders, and support automated analytics workflows for national security missions.

Analyzes internal and external marketing, sales, customer, and product data to develop predictive models, forecasts, dashboards, and actionable business insights. Builds data pipelines and BigQuery queries, performs data preparation and experimentation, and communicates findings through visualization tools. Guides generative AI adoption, develops AI agents and workflow automations, supports data governance, and partners with cross-functional teams to improve decision-making and marketing operations.

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.

Develop predictive analytics, machine learning models, AI services, and enterprise data science capabilities. Prepare and analyze complex datasets, implement LLM-based solutions, fine-tune and evaluate models, and collaborate with architects, cloud engineers, and product leaders on scalable analytics platforms. The role also supports architectural decisions, data-driven applications, dashboards, and sustainable development practices within a Department of State modernization program.

Develop machine learning, statistical, data-mining, graph-based, and heuristic algorithms for national security datasets. Build, optimize, and validate AI/ML and large language models; create feature vectors, experiments, simulations, visualizations, and automated analytics; and integrate prototypes into production analyst workflows. Collaborate with subject matter experts, evaluate models using statistical metrics, and guide analytic development efforts. The role requires an active TS/SCI clearance with polygraph.

Develops and maintains human capital data strategies, analytics, dashboards, and data science tools for U.S. Transportation Command. Applies predictive analytics, machine learning, and AI to workforce planning, recruitment, professional development, retention, and decision support. Builds analysis-ready data foundations, analyzes trends, maps data across secure and non-classified defense networks, improves existing tools, and collaborates with users, subject matter experts, and leadership. Requires Palantir Foundry experience, U.S. citizenship, and an active DoD Secret clearance.

Develop machine learning, statistical, data mining, graph-based, and heuristic algorithms for national security applications. Build and optimize AI/ML and large language models, including information retrieval workflows. Analyze varied datasets, create feature vectors, design experiments, evaluate models using standard metrics, produce visualizations, and translate subject matter expertise into production analytics. Guide analytic development efforts and integrate prototype algorithms into analyst workflows.

Leads data science and advanced analytics supporting Intelligence Community mission execution and national security objectives. Applies Python, R, Ruby, process automation, and large-scale data analysis to produce intelligence and targeting products. Collaborates with technical, executive, and government stakeholders, participates in peer reviews, and supports novel analytic methodologies. Oversees project operations, schedules, budgets, status reporting, issue resolution, and productivity goals. May lead teams through hiring, onboarding, performance management, and professional development.

Leads data science efforts supporting national security and Intelligence Community missions. Applies analytics and automation to large datasets, develops intelligence and targeting products, participates in advanced analytic peer reviews, and collaborates with technical, executive, and government stakeholders. Oversees project operations, schedules, budgets, status reporting, issue resolution, and productivity goals. May lead teams and support hiring, onboarding, and performance development.

Conduct workforce analytics and applied organizational research on attrition, mobility, engagement, performance, and planning. Analyze and validate HR data using SQL, R, or Python; apply statistical testing and regression; translate business questions into actionable insights; and communicate findings through visualizations, reports, and presentations. Partner with HR stakeholders while maintaining the accuracy, documentation, confidentiality, and integrity of sensitive workforce data.

Develops machine learning, statistical, data mining, graph-based, and large language models for national security applications. Analyzes datasets, creates feature vectors, prototypes and validates algorithms, builds experiments, generates visualizations, and implements analytics in production frameworks. The role collaborates with subject matter experts, optimizes GPU-based model training, supports LLM and RAG solutions, and guides analytic development efforts. An active TS/SCI clearance with polygraph is required.

Develop and operationalize machine learning, statistical, graph-based, and AI analytics for national security missions. Responsibilities include applied research, experimentation, data visualization, feature engineering, model development and validation, LLM and NLP optimization, GPU-accelerated computing, automation, production integration, and customer collaboration. The role also guides analytic efforts and translates complex data into actionable insights.

Entry-level Data Scientist who will frame business and technical problems, prepare and validate data, build and evaluate statistical and machine-learning models, and communicate findings through visualizations and presentations. The role includes collaborating with engineering and product teams to develop reusable, monitored analytical solutions, maintaining reproducible workflows, and addressing data governance, cybersecurity, bias, and Responsible AI requirements. Candidates will develop expertise in energy, engineering, and industrial applications through practical projects and mentorship.

Develops fraud prevention rules and strategies using advanced analytics, statistics, structured and unstructured data. Manages fraud strategy projects, governance, data structures, stakeholder reporting, vendor relationships, and risk mitigation processes. Translates business requirements into analytical solutions, validates scalable analyses, monitors industry trends, and recommends strategies to business partners.

Leads data science initiatives by analyzing complex structured and unstructured datasets, developing algorithms, processing data, creating visualizations and dashboards, and delivering data-driven insights to clients. Uses Python, SQL, ETL processes, APIs, and machine learning techniques while guiding teammates and communicating findings to technical and nontechnical audiences.

Develop data products and analytical solutions supporting USSPACECOM. Responsibilities include building pipelines in Foundry and Databricks, applying SQL, Python, PySpark, and TypeScript, designing ontologies and data models, creating statistical and decision-support tools, validating data quality, developing dashboards and workflows, and briefing findings to technical and senior non-technical stakeholders.

Develops advanced analytics for national security using large, disparate datasets. Responsibilities include designing data exploitation methods, researching sponsor inquiries, developing custom searches, applying classification, regression, clustering, and anomaly detection algorithms, and supporting threat hunting and malicious-activity detection. The role also involves statistical analysis, data visualization for nontechnical audiences, and prototyping data engineering pipelines.

Lead marketing effectiveness, experimentation, causal inference, predictive modeling, attribution, funnel measurement, and customer analytics. Build production-quality datasets, features, and models; assess data quality and instrumentation; communicate uncertainty and recommendations to executives; and coach analysts on reproducible, responsible methods. The role influences marketing investment, customer targeting, revenue, and enterprise priorities across travel, finance, operations, and customer experience.

Lead computational analysis for research on intrinsically disordered proteins and regions. Develop reproducible pipelines, integrate HDX-MS, interactomics, cryo-EM, and molecular-dynamics datasets, apply statistical and machine-learning methods, create visualization tools, support experimental design, and collaborate with structural biology, proteomics, and computational modeling teams. Contribute to publications, technical reports, and open computational resources.

Build Way’s data and intelligence layer across pricing, merchandising, personalization, forecasting, recommendations, and automation. Own data foundations, metrics, models, experiments, and production-ready datasets while partnering with Product and Engineering. Identify high-impact opportunities, ship measurable solutions, and establish rigorous, responsible data practices in a fast-moving startup environment.

Build Way’s data and intelligence layer from the ground up. Own data foundations, metrics, models, experiments, forecasting, recommendations, and decision systems across pricing, merchandising, personalization, and automation. Partner with Product and Engineering to transform ambiguous business problems into rigorous, production-ready solutions, while establishing reliable data products and responsible analytical practices.

Leads hands-on data science projects analyzing sensor, camera, and multimodal data to understand human movement and athletic performance. Applies machine learning, computer vision, signal processing, and statistical modeling; designs validated analytical workflows; builds reproducible software, datasets, and pipelines; coordinates technical execution; communicates limitations and tradeoffs; and mentors contributors across scientific and engineering teams.

Leads data science strategy across Digital Turbine’s mobile advertising marketplace. Designs experimentation frameworks, causal inference methodologies, and production machine learning models for bidding, audience segmentation, lifetime value, attribution, forecasting, and recommendations. Partners with engineering on deployment and monitoring, establishes scalable data science standards, mentors scientists, and communicates technical insights to executives. Requires extensive experience in data science or machine learning, advanced statistical expertise, cloud-scale data processing, and cross-functional technical leadership.

Develop scalable data science solutions for large structured and unstructured datasets supporting national security missions. Automate data processing, build machine learning and graph-based capabilities, and integrate LLMs into knowledge management workflows. Translate customer needs into analytical solutions, communicate findings through reports and visualizations, deploy models with engineering teams, and mentor junior data scientists. The role is full-time onsite in Reston, Virginia and requires an active TS/SCI clearance with CI polygraph.