Data Configuration Management Specialist

Insight Global is seeking a Database Configuration Management Specialist in Suffolk, VA. This team supports the Joint Training AI Realism & Acceleration effort by ensuring training, simulation, and AI systems are built on consistent, high-quality, and interoperable data. They design and maintain data standards, schemas, and pipelines that allow operational, exercise, and analytics data to be reliably integrated across joint training tools and AI/ML environments. The team's work enables accurate simulation behavior, advanced analytics, and AI-driven insights by making sure the right data is available, governed, and usable throughout the training lifecycle., * Lead end-to-end data science workflows, including problem formulation, data acquisition, feature engineering, model development, evaluation, deployment, and lifecycle monitoring.

• Translate operational and training objectives into data-driven solutions by defining data requirements and analytical approaches for integrating advanced AI/ML models into JTSE and Joint Training Tools.
• Design and maintain scalable data pipelines and architectures that support real-time and near-real-time ingestion, processing, and analysis of operational and test & evaluation data.
• Develop, train, and fine-tune machine learning models (including large-scale and foundation models) to enhance simulation, decision support, and training outcomes.
• Ensure data interoperability and consistency across multiple sources, systems, and stakeholders within a unified analytics environment.
• Integrate AI/ML models into simulation and synthetic environments, including Fully Informed Simulation Environment (FISE), to enable advanced analytics and scenario generation.
• Define and enforce data standards, schemas, and governance practices to ensure data quality, usability, and compliance.
• Support exercise planning, execution, and after-action analysis by enabling robust data collection, synchronization, and advanced analytics (predictive modeling, anomaly detection, performance metrics).
• Collaborate with cross-functional teams across government, industry, and mission partners to align analytical solutions with operational needs and modernization goals.
• Conduct model validation, testing, and performance evaluation to ensure accuracy, robustness, and mission relevance.
• Identify and mitigate risks related to data quality, model bias, scalability, and performance.
• Support MLOps/DevSecOps practices to enable secure, reproducible, and continuous delivery of data science solutions.
• Document data pipelines, models, methodologies, and analytical findings for technical and non-technical stakeholders.

• 5 years relevant experience with Bachelors in related field; 3 years relevant experience with Masters in related field; 0 years relevant experience with PhD or Juris Doctorate in related field; or High School Diploma or equivalent and 9 years relevant experience.
• Experience building and deploying machine learning or statistical models in production or operational environments.
• Strong knowledge of data processing, data architectures, and distributed data systems.
• Proficiency in programming languages such as Python or R and familiarity with common data science libraries.
• Experience with data wrangling, feature engineering, and exploratory data analysis.
• Understanding of AI/ML concepts, including supervised/unsupervised learning and model evaluation techniques.
• Experience creating technical documentation for models, datasets, and workflows.
• Ability to work in cross-functional teams and manage multiple priorities.
• Strong analytical thinking and problem-solving skills.
• Experience working in Linux-based environments. · Experience developing or fine-tuning large-scale or foundation models (LLMs, multimodal models).
• Familiarity with modern AI/ML frameworks.
• Experience deploying ML models into production systems or enterprise environments.
• Knowledge of real-time data processing and streaming technologies (Kafka).
• Familiarity with Joint Training and Simulation environments such as JTSE, JLVC, or similar DoD systems.
• Understanding of data governance, data standards, and enterprise data strategy.
• Experience with simulation data or synthetic environments.
• Familiarity with MLOps/DevSecOps pipelines and secure model deployment.
• Experience supporting joint, multi-domain, or coalition operations.
• Relevant certifications (AWS, Kubernetes, Security+, CISSP, or similar).

$48/hr to $50/hr.

Exact compensation may vary based on several factors, including skills, experience, and education.

Benefit packages for this role will start on the 31st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.