Data Scientist

Location: Amarillo, TX - Pantex Plant Job Title: Data Scientist Career Level From: Senior Associate Career Level To: Senior Specialist Organization: NSE Integration Services (51130643) Job Specialty: System Development

A career at Pantex can offer you the opportunity to make a personal impact on our nation. We recognize that excellent employees are absolutely critical for mission success. We are seeking an advanced Data Scientist to develop, validate, and deploy statistical models and machine learning algorithms that drive mission-critical insights, operational efficiency, and advanced forecasting capabilities. Primary duties include applying statistical methods and machine learning principles to analyze complex datasets, build predictive and prescriptive models for operational improvement, and translate high-value business problems into tangible, data-driven solutions. Additional duties may include conducting advanced research into new Artificial Intelligence (AI)/Machine Learning (ML) techniques, collaborating with Data Engineers and Machine Learning Operatons (MLOps) teams to deploy models, and presenting complex analytical findings to technical and non-technical stakeholders. Core

And Duties • Design, implement, and validate Machine Learning and statistical models for high-impact use cases, including predictive maintenance systems, resource optimization algorithms, and advanced forecasting. • Design and manage the MLOps process for models, including containerization, automated testing, and deployment using MLOps platforms and Continuous Integration (CI)/Continuous Deployment (CD) pipelines to transition models from development to a secure, live environment. • Maintain and monitor deployed models in production, rapidly diagnosing and resolving issues, managing data drift and model drift, and retraining models to ensure sustained performance and reliability. • Utilize advanced statistical and algorithmic techniques to perform comprehensive data analysis, identify trends, anomalies, and critical patterns in large, complex operational, safety, and financial datasets. • Partner with business units to define problem statements, gather data