Senior Data Scientist

Responsibilities for this Position

Location: USA FL MacDill AFB
Full Part/Time: Full time
Job Req: RQ221690

Type of Requisition:
Regular

Clearance Level Must Currently Possess:
Top Secret

Clearance Level Must Be Able to Obtain:
Top Secret/SCI

Public Trust/Other Required:
None

Job Family:
Data Science and Data Engineering

Job Qualifications:

Skills:
AI Frameworks, Applied Problem Solving, Data Compliance, Machine Learning Model Development
Certifications:
None
Experience:
8 + years of related experience
US Citizenship Required:
Yes

Job Description:

We are seeking a Senior Data Scientist to design, train, evaluate, and deliver machine learning models that solve operational problems across USCENTCOM's Data Office initiatives. This is a hands-on ML practitioner role-not a platform or infrastructure position. The Senior Data Scientist will work within an established on-premises Data Analytical Environment (DAE) built on a Data Lakehouse architecture with H100 GPU infrastructure, applying their expertise in statistical modeling, deep learning, and applied ML to turn enterprise data into actionable intelligence. The ideal candidate brings deep experience in model development across multiple problem domains-forecasting, NLP, anomaly detection, and classification-and can independently lead the ML practice for the team.

WHAT YOU WILL BE DOING:

Model Development & Training

• 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

MLOps & Lifecycle (Collaborative)

• 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

WHAT YOU WILL NEED:

Education & Experience

• 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

DESIRED QUALIFICATIONS

• 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)

WHAT GDIT CAN OFFER :

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

#ARMA

#GDITPRIORITY

#CENTCOM/CITS

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.

Scheduled Weekly Hours:
40

Travel Required:
Less than 10%

Telecommuting Options:
Onsite

Work Location:
USA FL MacDill AFB

Additional Work Locations:

Total Rewards at GDIT:
Our benefits package for all US-based employees includes a variety of medical plan options, some with Health Savings Accounts, dental plan options, a vision plan, and a 401(k) plan offering the ability to contribute both pre and post-tax dollars up to the IRS annual limits and receive a company match. To encourage work/life balance, GDIT offers employees full flex work weeks where possible and a variety of paid time off plans, including vacation, sick and personal time, holidays, paid parental, military, bereavement and jury duty leave. To ensure our employees are able to protect their income, other offerings such as short and long-term disability benefits, life, accidental death and dismemberment, personal accident, critical illness and business travel and accident insurance are provided or available. We regularly review our Total Rewards package to ensure our offerings are competitive and reflect what our employees have told us they value most.

We are GDIT. A global technology and professional services company that delivers consulting, 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 50 countries worldwide, offering leading capabilities in digital modernization, AI/ML, Cloud, Cyber and application development. Together with our clients, we strive to create a safer, smarter world by harnessing the power of deep expertise and advanced technology.

Join our Talent Community to stay up to date on our career opportunities and events at
gdit.com/tc .

Equal Opportunity Employer / Individuals with Disabilities / Protected Veterans

PI285157852

We are seeking a Senior Data Scientist to design, train, evaluate, and deliver machine learning models that solve operational problems across USCENTCOM's Data Office initiatives. This is a hands-on ML practitioner role-not a platform or infrastructure position. The Senior Data Scientist will work within an established on-premises Data Analytical Environment (DAE) built on a Data Lakehouse architecture with H100 GPU infrastructure, applying their expertise in statistical modeling, deep learning, and applied ML to turn enterprise data into actionable intelligence. The ideal candidate brings deep experience in model development across multiple problem domains-forecasting, NLP, anomaly detection, and classification-and can independently lead the ML practice for the team.



WHAT YOU WILL BE DOING:



Model Development & Training

• 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

MLOps & Lifecycle (Collaborative)

• 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

WHAT YOU WILL NEED:



Education & Experience

• 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

DESIRED QUALIFICATIONS

• 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)

WHAT GDIT CAN OFFER :


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