Geo Data Scientist

Leidos is seeking an exceptional and motivated Geo Data Scientist to work alongside world class engineers and researchers supporting the mission of the U.S. Department of Energy’s (DOE) National Energy Technology Laboratory (NETL). This position is expected to be a hybrid position, based in Albany, OR. This work will involve a multi-disciplinary, scientific, and technically oriented national laboratory team, with participation alongside other data scientists, engineers, geologists, and computer scientists that produces technological solutions for America’s energy challenges. Fully remote work may be possible. From developing creative innovations and efficient energy systems, to advancing technologies that enhance oil and natural gas extraction and transmission processes, NETL research is providing breakthroughs and discoveries that support home-grown energy initiatives, stimulate a growing economy, and improve the health, safety, and security of all Americans. Highly skilled professionals at NETL’s three research sites – Albany, Oregon; Morgantown, West Virginia, and Pittsburgh, Pennsylvania – conduct a broad range of research activities that support DOE’s mission to advance the national, economic, and energy security of the United States.

What this opportunity with Leidos supporting NETL uniquely provides you: 

• Working on applied, cutting-edge projects with global impact while being mentored by the nation’s leading energy scientists and engineers.   
• Real-world experience supplemented with technical development and discussions that provide unique insight into the broad range of mission critical engineering and scientific disciplines NETL leverages to support national energy research and policy development.  
• Access to world-class, customized facilities and computational assets specific to high impact energy research, technology generation, and product development.  
• Support proposal development focused on expanding industry and scientific partnerships and developing new technical opportunities for NETL with federal guidance.  

Primary Responsibilities:

• Utilize geologic, geochemical, and geophysical data to develop testable hypotheses on the occurrence and distribution of energy and mineral resources in geologic systems.  
• Develop and apply computational geodata science methods to augment geospatial analysis.  
• Apply statistical and geostatistical analysis for a variety of energy-related topics.  
• Develop, query, manage, and maintain contextual and spatial databases, and structure/restructure existing databases for a range of experimental and spatial uses.  
• Utilize Python (version 3+) to acquire, process, and analyze spatial and non-spatial multivariate data, as well as develop data analysis and visualization tools.  
• Collaborate with multidisciplinary group of science researchers to accomplish project tasks  
• Build relationships with internal and external clients.  

• Lead and assist in the writing of science-based methods, results, and data interpretations for publications in high quality, scientific peer-reviewed journals, and technical reports. 
• Develop and present results for oral presentations to staff, stakeholders, and at professional conferences. 
• Provide weekly and monthly technical updates to research team members and project management. 
• Provide leadership and expertise on projects including delegation to team members and communication of project milestone status to management. 
• Effectively document and communicate scientific results through peer-review journal manuscripts and technical reports.   

Required Education, Experience & Other:

• Master’s degree in geology, applied computer science, geospatial science, computational geology, geo-statistics, spatial statistics, geography, or similar field with 7+ years’ experience in energy related R&D
• Proficiency with Python for advanced coding needs, including using Python to automate analysis and build data visualization tools
• Evidence of innovation in statistical methods applied to geospatial statistical analyses and other forms of multivariate analysis
• Understanding of and experience in spatial and/or subsurface topics
• Demonstrated skills in the application of statistical analyses, AI/ML methods, or other forms of multivariate analyses to