Data Science Engineer 1 AI Development
At BWX Technologies, Inc. (NYSE: BWXT), we are People Strong, Innovation Driven. Headquartered in Lynchburg, Va., BWXT provides safe and effective nuclear solutions for national security, clean energy, environmental remediation, nuclear medicine and space exploration. With approximately 6,400 employees, BWXT has 12 major operating sites in the U.S. and Canada. We are the sole manufacturer of naval nuclear reactors for U.S. submarines and aircraft carriers. Our company supplies precision manufactured components, services and fuel for the commercial nuclear power industry across four continents. Our joint ventures provide environmental remediation and nuclear operations management at more than a dozen U.S. Department of Energy and NASA facilities. BWXT’s technology is driving advances in medical radioisotope production in North America and microreactors for various defense and space applications. Follow us on Twitter at @BWXTech and learn more at . BWXT’s Nuclear Operations Group - Lynchburg is currently seeking a Data Science Engineer for its Lynchburg, VA location! BWXT's Welding Manufacturing Operations section is seeking a highly skilled Data Scientist to join our Welding Engineering group. This group generates vast amounts of electronic data for a variety of welding processes and applications. This role will be instrumental in setting up data warehouses, monitoring processes, and advancing Al applications in welding manufacturing operations. The ideal candidate will have expertise in data science, machine learning, and industrial process optimization, with a focus on leveraging Al to enhance welding efficiency, quality and predictive maintenance. Key Responsibilities
- Data infrastructure and warehousing
- Design, develop, and maintain data warehouses to store and manage large-scale welding operations data
- Ensure seamless integration of data from various sources, including sensors, PLCs, and production databases
- Implement ETL (Extract, Transform, Load) processes for efficient data extraction and processing
- Develop and deploy real-time monitoring systems to track key welding parameters to detect and report anomalies
- Analyze sensor and machine data to improve weld quality, defect detection, and predictive maintenance
- Utilize statistical models, Al, and ML techniques to enhance process control and automation
- Develop Al-driven solutions to predict weld defects, optimize settings, andimprove process consistency
- Implement computer vision techniques for weld quality inspection and automation
- Leverage deep learning and reinforcement learning to optimize robotic welding systems
- Create dashboards and visualization tools to provide insights into production efficiency and quality
- Perform exploratory data analysis and present findings to engineers, production teams, and leadership
- Assist in root cause analysis by correlating welding data with production outcomes
- Work closely with welding engineers, automation specialists, and IT teams to enhance manufacturing intelligence
- Remain updated on emerging Al and data science technologies relevant to industrial welding
- Provide guidance on best practices for data governance, security and compliance
- Bachelor's degree in Data Science, Computer Science, Engineering, Statistics or related field
- Must be a US citizen with no dual citizenship
- Must be able to obtain and maintain a U.S. Department of Energy (DOE) clearance CVAA,
- Proficiency in Python, R, SQL and big data technologies
- Knowledge or experience with machine learning frameworks (TensorFlow, PyTorch, Scikit-learn) - Knowledge of industrial loT and sensor data processing
- Familiarity with data warehousing tools, e.g., Microsoft SQL Server
- Knowledge or experience with predictive modeling, time-series forecasting, and anomaly detection
- Knowledge or experience in computer vision for industrial applications is a plus
- Dashboard creation with Power BI would be a plus
- Knowledge of web technologies (for example REST APIs) and frameworks (e.g. React, Vue.js) would be a plus
- Knowledge of C# would be a plus
- Understanding of welding processes, materials, and quality control (preferred, but not mandatory)
- Previous experience in manufacturing, automation, or industrial analytics is highly desirable, but not mandatory
- Knowledge of Six Sigma, Lean Manufacturing, or process optimization techniques is a plus
- Strong problem-solving skills with an analytical mindset
- Ability to communicate complex data insights to technical and non-technical stakeholders
- A team player with a collaborative approach to interdisciplinary projects
- Must possess proven ability and willingness to learn new tools
- Must be able to demonstrate superior written, oral, and interpersonal communication skills
- Must be highly self-motivated and directed, with keen attention to detail
- Certifications in data science, Al, or cloud computing (AWS Certified Machine Learning, Google Professional Data Engineer, etc.)
- Master's in Data Science Preferred
- Experience with robotic and mechanized welding systems and automation
- Understanding of edge computing for real-time data processing
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