Data Scientist

Location:

Suffolk, VA, Virginia, United States

Requisition Number:27918

Required Travel: 0 - 10%

Employment Type:

Full Time/Salaried/Exempt

Anticipated Salary Range:$-$

Security Clearance:

Secret

Level of

Experience:

Senior

This opportunity resides with Global Security (GS). Mission Technologies’ Global Security (GS) group comprises live, virtual, constructive (LVC) solutions; fleet sustainment; nuclear and environmental; and Australia business.

As a trusted partner to our military customers, HII designs, develops and operates the largest LVC enterprise that prepares warfighters for cross-domain battle. With advanced technologies to enable mission readiness, HII understands that preparation requires full coordination—not readiness in piece-parts.

For more than 40 years, the U.S. Navy has entrusted HII to maintain and modernize the vast majority of its fleet. With a holistic approach to life‑cycle maritime defense systems—from small watercraft to submarines, surface combatants and aircraft carriers—HII ensures a high state of readiness.

HII supports the Department of Energy’s national security mission through the management and operation of its sites, as well as the safe cleanup of legacy waste across the country. HII meets clients’ toughest nuclear and environmental challenges.

Leadership at HII is a mindset, not a title. Through our Leadership Capability Framework, we define how every team member contributes to our mission and culture:

• Know & Grow Your People
  – Commit to learning and supporting team success.
• Build Relationships
  – Communicate openly, collaborate well, and build trust.
• Take Ownership
  – Deliver on commitments and take pride in your work.
• Customer First
  – Focus on the mission and those we serve.
• Shape the Future
  – Bring ideas, curiosity, and continuous improvement.
• Act with Urgency
  – Take initiative and follow through with purpose.

These capabilities guide how all employees contribute to our shared success across Mission Technologies.

Mission Technologies, a division of Huntington Ingalls Industries, is seeking a Data Scientist to support the Joint Training Synthetic Environment (JTSE) and JLVC Modernization effort under the Joint Staff J7 (JS J
7) contract. This role focuses on developing advanced analytics, AI/ML models, and data architectures that enhance joint training, simulation, and decision support capabilities.

• Lead end to end data science workflows, including problem definition, data acquisition, feature engineering, model development, evaluation, deployment, and lifecycle monitoring.
• Translate operational and training objectives into data driven solutions by defining analytical approaches and data requirements 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 fidelity, decision support, and training outcomes.
• Ensure data consistency and interoperability across multiple sources, systems, and stakeholders within a unified analytics environment.
• Integrate AI/ML models into simulation and synthetic environments, including the Fully Informed Simulation Environment (FISE), to support advanced analytics and dynamic scenario generation.
• Define, implement, and enforce data standards, schemas, and governance practices to ensure data quality and compliance.
• Support exercise planning, execution, and after action analysis by enabling predictive analytics, anomaly detection, performance metrics, and other advanced analyses.
• Collaborate with cross functional teams — including government stakeholders and mission partners — to align data science solutions with operational requirements and modernization goals.
• Conduct model validation, testing, and performance assessments to ensure accuracy, robustness, and mission alignment.
• Identify and mitigate risks related to data quality, model bias, scalability, and operational performance.
• Support MLOps/Dev Sec Ops  practices to enable…