Top Data Science Jobs

Develop AI tools, machine learning systems, predictive analytics, data visualizations, and large-scale Multi-INT data fusion capabilities for USCYBERCOM J2 intelligence operations. Analyze and merge disparate data using R, Python, and SQL; create Power BI and Tableau visualizations; produce analytic reports; and collaborate with intelligence stakeholders to prioritize capability gaps.

Analyze complex structured and unstructured data; design data pipelines; develop predictive, prescriptive, NLP, clustering, forecasting, and machine learning models; automate data processing; use cloud and distributed computing platforms; create visualizations; collaborate with data engineers; research algorithms; and communicate insights to nontechnical audiences supporting U.S. Special Operations Command.

Leverage complex structured and unstructured data to support U.S. Special Operations Command decision-making and digital transformation. Design and maintain data pipelines, perform statistical analysis, develop predictive and prescriptive models, and implement machine learning, NLP, forecasting, clustering, and text-processing solutions. Use cloud data platforms and distributed processing frameworks to integrate, analyze, and visualize data. Collaborate with data engineers, communicate findings to nontechnical audiences, and support mission readiness initiatives.

Develop and lead image and video generative AI pipelines, including model fine-tuning, multimodal workflows, agentic orchestration, and visual quality evaluation. Collaborate with Creative, Product, and Engineering teams to deliver scalable AI solutions for product imagery, virtual try-on, and digital content. Evaluate emerging models and vendors, guide data curation, and help productionize research prototypes into cost-effective services and APIs.

Design and deploy deep learning systems for search ranking, personalized recommendations, geospatial search, and pickup-point selection. Translate business goals into ML objectives, lead offline and online evaluation, conduct A/B tests, and partner with engineering on production model serving and latency optimization. Own the production ML lifecycle, including monitoring, drift detection, retraining pipelines, and quality management across international markets.

Develop and operationalize machine learning and statistical models predicting weather-driven transmission and distribution outages. Integrate weather forecasts, infrastructure data, outage records, and geospatial layers into real-time forecasting pipelines. Apply spatio-temporal, probabilistic, and physics-based modeling to support utility decisions during extreme weather and wildfire events. Collaborate with meteorologists, risk modelers, software engineers, and utility customers while using agentic coding tools to accelerate development and validating scientific correctness.

Develop and deploy statistical and machine learning models supporting credit risk, fraud, collections, and marketing. Responsibilities include data exploration, model design, testing, production monitoring, performance analysis, governance, and stakeholder communication. The role partners with Legal and Compliance, translates business questions into analytical solutions, researches new methods, and provides data-driven recommendations to leadership.

Lead data science for Search & Discovery: analyze customer search interactions, design and measure experiments, build datasets and analytics pipelines, and optimize ML/LLM ranking models to improve relevance and personalization.

Lead end-to-end delivery of strategic data science and AI solutions for AI infrastructure. Work with telemetry and experimentation at fleet scale to build, deploy, and measure predictive and prescriptive models. Partner with stakeholders, present insights, enable adoption, and promote responsible AI. Collaborate closely with data engineers and infrastructure teams to productionize scalable ML solutions.

The Sr. Data Scientist will design and optimize intelligent search solutions using Elasticsearch and GenAI technologies, improving data retrieval and search relevance for enterprise applications.

Leads analytical and technical execution for member onboarding and customer experience portfolios. Develops advanced analytics, predictive models, causal inference, experimentation, AI/ML, and LLM solutions using Python and SQL. Owns solution design, measurement, testing, and performance evaluation while partnering with cross-functional stakeholders. Mentors data scientists, communicates trade-offs, and applies analytical rigor to improve engagement, satisfaction, retention, and healthcare experiences.

Develops scalable data science and analytic solutions using large, disparate datasets. Responsibilities include statistical and machine learning analysis, entity resolution, graph and relational analytics, data profiling, validation, dashboards, reusable workflows, and operational tooling. The role translates complex findings into decision-ready insights, collaborates with analysts and engineers, documents methodologies, and transitions prototypes into reliable capabilities for government mission requirements.

Develops repeatable data science and analytic solutions from large, disparate datasets. Responsibilities include exploratory analysis, data quality assessment, statistical and machine learning modeling, entity resolution, relationship discovery, validation, dashboards, reusable pipelines, and analyst-ready insights. The role collaborates with multidisciplinary teams to transition prototypes into reliable operational capabilities, documents methodologies and limitations, and supports mission-critical government requirements.

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.

The Data Scientist will design and deploy AI-enabled data solutions, developing data pipelines and collaborating with teams to transform data into insights.

Design and implement data models, algorithms, ETL pipelines, and analytics solutions. Analyze large structured and unstructured datasets using Python/R and data science libraries, validate integrations, build visualizations and dashboards, and collaborate with stakeholders to deliver mission-focused insights for Army modernization.

The Data Scientist will apply advanced statistics and machine learning to solve cybersecurity challenges, develop prototypes, and present findings. Collaboration with government and academia is key.

As a Senior Staff Data Scientist, you will lead data science initiatives, mentor teams, develop frameworks for experimentation, and collaborate across departments to drive decision-making through data insights.

The Data Scientist supports customer use of the Epistemix platform through data integration, modeling, and visualization, improving decision-making and customer satisfaction.

As a Senior Data Scientist, you'll analyze complex data to support NGA, develop scalable Python solutions, and integrate findings into mission workflows for decision-making.

As a Data Scientist, you will analyze complex data sets, build machine learning models, and work in a team to provide solutions, ensuring data security and optimization.

The Data Scientist will analyze complex data, build predictive models, and collaborate with teams to innovate technical solutions and optimize processes.

The Senior Data Scientist will develop data pipelines for AI applications, optimize data structures, manage databases, and ensure data quality and security.

Lead people analytics by building dashboards and predictive models across the employee lifecycle. Apply advanced statistical methods, NLP/GenAI, and survival/forecasting analyses to surface insights on attrition, skills gaps, performance, and org health. Drive data governance, ensure privacy/PII controls, enable self-service analytics, and partner with HR, TA, Finance, IT, and senior leaders to inform workforce planning and strategic decisions.

The Data Scientist Level 3 will use mathematical, statistical, and computational skills to analyze large datasets, derive insights, and communicate results to both technical and non-technical audiences.