Data Scientist 3

Role Overview

• 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/DevSecOps practices to enable secure, repeatable, and continuous delivery of data science capabilities.
• Document data pipelines, models, methodologies, and analytical findings for technical and non technical audiences

Requirements

• 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.
• Ability to obtain and maintain a Secret Clearance within 45 days of hire.
• Experience building and deploying machine learning or statistical models in production or operational environments.
• Strong knowledge of data processing, distributed data systems, and data architecture principles.
• Proficiency in Python or R and experience with common data science libraries and toolkits.
• Experience with data wrangling, feature engineering, and exploratory data analysis.
• Understanding of AI/ML concepts including supervised/unsupervised learning, model evaluation, and performance metrics.
• Experience preparing and maintaining technical documentation for datasets, models, and analytical workflows.
• Ability to work within cross functional teams and manage multiple priorities.
• Strong analytical reasoning and problem solving skills.
• Experience working in Linux based environments.

Tech Stack

• Linux
• Python

Benefits

• best-in-class medical, dental and vision plan choices
• wellness resources
• employee assistance programs
• Savings Plan Options (401(k))
• financial planning tools
• life insurance
• employee discounts
• paid holidays
• paid time off
• tuition reimbursement
• early childhood and post-secondary education scholarships