> Markdown version of [/jobs/ext/3896866-data-scientist-senior-ts-sci-w-poly](https://www.wearedevelopers.com/jobs/ext/3896866-data-scientist-senior-ts-sci-w-poly). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist Senior - TS/SCI w/poly - **Company:** General Dynamics Information Technology - **Location:** Berwyn Heights, MD, United States (Remote available) - **Experience:** Expert - **Salary:** $111,155.0 - $150,385.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Business Analytics Applications, Microsoft Azure, Cloud Computing, Continuous Integration, Data Mining, Graph Database, Interoperability, Python (Programming Language), Knowledge Management, Machine Learning, Natural Language Processing, Named Entity Recognition, Performance Tuning, Tensorflow, Secure Coding, SPARQL, SQL Databases, Scripting, Pytorch, Large Language Models, Gitlab, Kubernetes, Optimization Algorithms, Graphql, Machine Learning Operations, Docker, Jenkins, Microservices - **Published:** October 23, 2026 - **Apply:** https://www.dice.com/job-detail/c8401a67-1794-4e56-853d-2e40b8392390 ## About the Role Analytical Thinking, Datasets, Machine Learning Methods, 17 + years of related experience, Apply prior experience in large-data multi-INT analytics, ML, and automated predictive analytics; hold a professional or graduate-level certificate in data science from a recognized institution., Master's degree with 12 years related experience or Bachelor's degree with 17 years' experience., Maintain or pursue preferred qualifications including Certified Kubernetes Administrator, cloud GovCloud (AWS/Azure Gov) experience, and RMF/security .training. ## Description GDIT delivers critical all-source intelligence on foreign military and civilian cyber actors, their supporting infrastructure, and the broader ecosystems in which these capabilities operate. This intelligence directly supports foundational military intelligence (FMI) requirements for the joint force and ensures alignment with the mission portfolios. On this program, GDIT provides a broad range of analytic and mission-enabling support to produce operationally relevant FMI and scientific and technical intelligence (S&TI) for cyberspace operations. Our support is not limited to analysis; we engage across the entire intelligence cycle-planning, collection, processing, exploitation, production, and dissemination-while also executing integrated mission management functions. All support is focused on enhancing the customers' ability to enable both defensive and offensive cyberspace operations., Job Requirement: Data Scientist (AI/ML Engineer) The Data Scientist (AI/ML Engineer) designs, implements, and secures production machine-learning systems to support classified intelligence missions. This role develops hardened ML architectures and microservices; implements containerized and clustered deployments; ensures compliance with RMF and OPSEC controls; optimizes models for constrained environments; and integrates AI/ML capabilities with mission systems and sensors. The engineer performs secure code and model handling, conducts performance tuning, automates secure build and deployment pipelines, and coordinates with security/SSO personnel to prevent inadvertent disclosure during agile prototyping. The position advances cutting-edge AI capabilities by designing and evaluating new analytic methods, conducting independent research, and incorporating emerging technologies to enhance all-source intelligence production, knowledge management, and analytic tradecraft. The Data Scientist leverages advanced statistical methods, develops semantic automation workflows, improves knowledge-graph reasoning, enhances entity extraction and summarization, and conducts multi-INT analytic augmentation through ML. This role also supports tool and workflow modernization, performs data-science scripting in R/Python/SQL, manages disparate data sources, and evaluates AI/ML techniques for risks, biases, and limitations. The Data Scientist contributes to incremental capability enhancements, maintains familiarity with state-of-the-art technologies, and produces analytic outputs on emerging military technologies worldwide. Responsibilities Design, implement, and secure production ML systems and deployments for classified environments, including hardened architectures, microservices, containerized/clustered deployments, RMF/OPSEC compliance, and integration with mission systems. Conduct secure code and model handling, performance tuning, and automation of secure CI/CD build and deployment pipelines; coordinate with SSO/security to prevent inadvertent disclosure during development. Design, develop, and evaluate leading-edge AI technologies for integration into all-source analysis tradecraft, assessments, production workflows, dissemination, and knowledge management. Propose and apply advanced statistical and mathematical techniques to support model formulation, experimental design, and development of new analytic methodologies. Collaborate with team members on exploratory efforts using large language models, NLP, and ML to automate ontologies and ensure semantic accuracy and interoperability with knowledge-graph architectures. Evaluate AI, data-science, and advanced analytic methods for risks, biases, and limitations that may distort analytic conclusions. Develop and refine semantic data-retrieval and reasoning capabilities across knowledge graphs using GraphQL, SPARQL, SHACL, SQL, and other query frameworks. Conduct continuous independent research on analytic methods and technologies across government, industry, and academia; inform senior leadership on applicability to mission programs. Apply in-depth knowledge of theories, techniques, and processes to investigate, prototype, and evaluate technologies that enhance all-source intelligence analysis. Support automation of entity extraction, recognition, and summarization using ML/NLP techniques in alignment with analytic tradecraft standards. Perform research studying how to augment or automate all-source analytic processes using computer-based models and AI/ML systems. Deliver incremental enhancements to analytic tools, capabilities, workflows, and methods. Write R or Python scripts, apply SQL, and manage and merge disparate datasets; perform statistical analysis and apply data-mining algorithms to support mission analytics. Utilize and maintain proficiency with tools such as TensorFlow/PyTorch, Docker, Kubernetes, CI/CD (Jenkins/GitLab), GPU/HPC workflows, secure software-development practices, and model-optimization techniques.