Data Scientist

• Design, train, and validate supervised, unsupervised, and deep learning models using open-source libraries (PyTorch, TensorFlow, Scikit-learn, XGBoost, LightGBM) to support forecasting, classification, anomaly detection, and NLP use cases
• Conduct rigorous experiment design: feature engineering, hyperparameter tuning, cross-validation, and evaluation using appropriate metrics (precision/recall/F1, RMSE, AUC-ROC) to ensure production-quality model performance
• Fine-tune and adapt open-source LLMs (LLMA, Mistral, and similar) for domain-specific tasks including document summarization, entity extraction, and question-answering over classified and unclassified networks
• Develop and maintain RAG pipelines: chunking strategies, embedding model selection, retrieval evaluation, and prompt engineering to deliver high-quality LLM-augmented analytics

Applied Problem-Solving

• Translate mission requirements into ML solutions: work directly with analysts, operators, and leadership to scope problems, define success criteria, and deliver models that produce actionable operational insights
• Build models across multiple domains including predictive analytics (logistics, readiness), NLP/text analytics (reports, intelligence documents), anomaly detection (cybersecurity, network, behavioral), and computer vision where applicable
• Design lightweight, optimized models for edge and disconnected environments when required, supporting model optimization and conversion (ONNX, TensorRT, OpenVINO) for tactical deployment, * Version, track, and reproduce experiments using MLflow, DVC, and Git; maintain clear documentation of model lineage, training data, and performance baselines
• Package trained models for deployment in containerized environments (Docker, Kubernetes) in coordination with the platform engineering team. Ownership of deployment infrastructure is flexible and project-dependent
• Integrate models into existing CI/CD pipelines, analytics platforms, and decision support tools in collaboration with the DevSecOps and data engineering teams

Data Security & Compliance

• Ensure all model development adheres to DoD security, encryption, and data handling standards, including tagging, metadata management, and retention policies
• Operate within classified environments (SIPR/NIPR), following cybersecurity and data stewardship protocols across air-gapped and hybrid infrastructure, Certified Entry Level Python Programmer (PCEP) | Python Institute (PI) - Python Institute (PI) Travel Required

Less than 10% Citizenship

• Bachelor's or Master's degree in Computer Science, Machine Learning, Statistics, Applied Mathematics, Data Science, or related quantitative field
• 8+ years of hands-on AI/ML model development experience with a strong record of delivering production models, not just prototypes
• Compliant with DoD Directive 8140 (i.e., CompTIA Security + CE cert)
• Active Secret clearance is required. Must be TS/SCI eligible
• Must be able to work on site at MacDill AFB. Not a remote role.

Technical Skills

• Strong Python proficiency and deep experience with open-source ML frameworks (PyTorch, TensorFlow, Scikit-learn, XGBoost, LightGBM, Hugging Face Transformers)
• Demonstrated ability to train, fine-tune, and evaluate models end-to-end-from raw data through feature engineering, model selection, training, validation, and production handoff
• Experience with LLM fine-tuning techniques (LoRA, QLoRA, PEFT) and RAG architecture design (vector databases, embedding strategies, retrieval evaluation)
• Working knowledge of MLOps toolchains (MLflow, DVC, Weights & Biases) and version control (Git).
• Familiarity with containerized deployment (Docker, Kubernetes) in air-gapped or on-premise environments
• Experience working with large-scale data systems and medallion/lakehouse architectures, * Experience with model optimization and conversion (ONNX, TensorRT, OpenVINO) for edge or tactical deployment
• Knowledge of NLP techniques applied to defense or intelligence domains (entity extraction, document classification, summarization of operational reports)
• Familiarity with distributed data frameworks (Apache Spark, Dask)
• Experience with edge AI hardware (NVIDIA Jetson, Coral TPU), Years of Experience

8 + years of related experience

• may vary based on technical training, certification(s), or degree Certification

Certified Data Scientist (Open CDS) | The Open Group - The Open Group

At GDIT, the mission is our purpose, and our people are at the center of everything we do.

• Growth: AI-powered career tool that identifies career steps and learning opportunities
• Support: An internal mobility team focused on helping you achieve your career goals
• Rewards: Comprehensive benefits and wellness packages, 401K with company match, competitive pay and paid time off
• Community: Award-winning culture of innovation and a military-friendly workplace, The likely salary range for this position is $153,000 - $207,000. This is not, however, a guarantee of compensation or salary. Rather, salary will be set based on experience, geographic location and possibly contractual requirements and could fall outside of this range.

Own your opportunity to support our nation's defense. Make an impact by connecting and securing critical operations across the globe, keeping our country safe and secure., We are GDIT. A global technology and professional services company that delivers technology and mission services to every major agency across the U.S. government, defense and intelligence community. Our 26,000 experts extract the power of technology to create immediate value and deliver solutions at the edge of innovation. We operate across over 50 countries worldwide, offering leading capabilities in digital modernization, AI/ML, cloud, cyber and application development. Together with our customers, we strive to create a safer, smarter world by harnessing the power of deep expertise and advanced technology.