Data Science & Analytics Technical Lead
at Agile Defense
Tampa, FL, onsite, senior, 5+ years
posted 30 Jun 2026
- Exploratory Data Analysis
- Natural Language Processing
- Feature Engineering
- Regression
- Model Validation
- Data Mining
- Clustering
- Machine Learning
- Recommendation Systems
- Hyperparameter Tuning
- Classification
- Statistical Analysis
About the role
Posted: 2026-06-30
About Agile Defense At Agile Defense we know that action defines the outcome and new challenges require new solutions. That’s why we always look to the future and embrace change with an unmovable spirit and the courage to build for what comes next. Our vision is to bring adaptive innovation to support our nation's most important missions through the seamless integration of advanced technologies, elite minds, and unparalleled agility—leveraging a foundation of speed, flexibility, and ingenuity to strengthen and protect our nation’s vital interests.
Requisition #: 1706 Job Title: Data Science & Analytics Technical Lead Clearance Level: Top Secret / SCI, Must Have Clearance to Start
The contractor shall identify a Data Science & Analytics Technical Lead by name who shall drive the strategic integration of advanced analytics capabilities across the SOF enterprise. This leadership role is centered on applying scientific methods, algorithms, and systems to transform vast quantities of both structured and unstructured data into actionalble insights and essential knowledge for the Head Quarters (HQ) Staff, Service Components, and TSOCs.
Job Duties
- Lead the design, development, and deployment of complex machine learning models, statistical analysis, and data mining techniques to solve advanced business problems.
- Build and improve predictive models for customer behavior, churn prediction, demand forecasting, and other business-critical areas.
- Conduct advanced exploratory data analysis (EDA) to uncover trends, patterns, and actionable insights from structured and unstructured data sources.
- Develop and implement algorithms for classification, regression, clustering, natural language processing (NLP), and recommendation systems.
- Collaborate closely with cross-functional teams, including data engineering, product, and business teams, to define data science objectives and translate them into actionable projects. Communicate technical results, findings, and recommendations to stakeholders at all levels, ensuring data-driven strategies are clearly understood and actionable.
- Lead efforts in feature engineering, hyperparameter tuning, and model validation to ensure high model accuracy, performance, and robustness. Evaluate and apply cutting-edge machine learning frameworks, tools, and techniques to optimize workflows and drive innovation.
- Mentor junior data scientists, providing technical guidance and promoting best practices in data science and machine learning.
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