Data Scientist

Headquartered in Lynchburg, Va., BWX Technologies, Inc. (NYSE:BWXT) is a leading supplier of nuclear components and fuel to the U.S. government; provides technical and management services to support the U.S. government in the operation of complex facilities and environmental remediation activities; and supplies precision manufactured components, services and fuel for the commercial nuclear power industry. With approximately 6,100 employees, BWXT has nine major operating sites in the U.S. and Canada. In addition, BWXT joint ventures provide management and operations at a dozen U.S. Department of Energy and two NASA facilities. Follow us on Twitter @BWXTech and learn more at www.bwxt.com. 

BWXT is currently seeking a, multi-talented Engineering Data Scientist to serve as a lead researcher for nuclear product development for its location in Lynchburg, VA.

• Job Description/Duties:
• Combines engineering or technical skill with data science techniques to enhance insights or implement machine learning for design, research, or production systems.
• Deploys a range of data science techniques from statistical analyses to learning systems as appropriate to structured and unstructured data
• Develops and deploys code and and a range of data science techniques on data engineering platforms making use of historical data sets or collected via instrumentation of development or production processes.
• Lends data science expertise to other BWXT projects across the enterprise from ideation and scoping to commercialization that include power systems, chemical processing, and computer vision for manufacturing.  
• Satisfies research and development objectives to warrant continued investment toward product realization, both as research investigator creating new innovations and as support to engineers.

• Job Qualifications/Requirements:
• A minimum of a Bachelor’s Degree in a technical or computational field of study (e.g., nuclear engineering or design, statistics, bioinformatics, chemical engineering, electrical engineering, computer or software engineering. An Engineering Degree must be from an ABET-accredited university.
• A minimum of 10 years of experience is required, however, an advanced degree may substitute for some years of experience.  A Master's Degree or project experience employing multi-variable, multi-variate regression techniques and machine learning methods is preferred.
• Strong C++, Python, and/or R analytical programming is required. The candidate must possess strong coding skills.  
• Project experience and skills in relevant technical field may substitute for some machine learning experience, but a foundational education in statistics and data science techniques to go along with background in software or computer engineering, electrical engineering, nuclear analysis and design, or other technical field is required.  The successful candidate with a solid data science foundation and relevant technical background will have the opportunity for continued immersion and data science technique skill refinement.
• Practice creating general linear and non-linear data models, Monte Carlo simulation, Gaussian mixture models, k-means clustering, hierarchical clustering, and/or support vector machine applications preferred. 
• Image processing, computer vision, and convolutional neural network algorithm development and filter modification skills is desired, using OpenCV, Tensorflow and similar packages is a plus.
• Must be a US Citizen with no dual citizenship

BWX Technologies, Inc. (BWXT) embraces diversity of thought, values individuality, encourages new perspectives and provides equal opportunity in employment for all qualified employees and applicants without regard to race, color, religion, gender, sexual orientation, age, national origin, disability, veteran status, genetic information, or any other category protected by federal, state, and/or local law.

https://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf

https://www.dol.gov/ofccp/regs/compliance/posters/pdf/OFCCP_EEO_Supplement_Final_JRF_QA_508c.pdf