Leidos is hiring an exceptional and motivated Geospatial 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) 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.
This position is onsite at the NETL campus in Albany, OR.
What this opportunity with Leidos supporting NETL through a Research Support Services (RSS) contract 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.
The successful candidate will participate in research focused on Critical Minerals and Materials (CMM) resources. This includes evaluation of unconventional rare earth element (REE) feedstocks of domestic sedimentary basins and providing mineral system expertise for AI/ML-driven methodologies for prediction of CMM in unconventional prospects.
The ideal candidate will have a background in geospatial systems and strong programming skills. They will also have familiarity with natural resource exploration, geochemistry, and geology (including sedimentary systems). Experience relating to critical minerals and national laboratory research is preferred.
Primary Responsibilities:
- Support the identification, acquisition, processing, and integration of non-spatial and spatial data using Geographic Information System (GIS) software and Python scripting.
- Identify credible data sources through extensive literature reviews and online research, then acquire and process data for further analytics.
- Support quality assurance and control of geospatial data products and associated metadata prior to public release following FAIR Principles.
- Support scientific, spatial, and statistical analytics, as well as utilize appropriate artificial intelligence and machine learning algorithms to support energy research.
- Collaborate with an interdisciplinary team, including geologists, geographers, chemists, computer scientists, environmental scientists, and other researchers to assist each other in accomplishing project related tasks.
- Build and maintain 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.
Requirements:
- Must be able to meet the requirements for gaining access to work on the NETL campus
- Must be a U.S. Citizen
- Master’s degree in Geography, Environmental Sciences, Data Science, Petroleum Engineering, or related field with 3+ years relevant work experience programming in Python for non-spatial and spatial data acquisition, processing, and analytics
- Competent in non-spatial and spatial data management, handling, and analytics using GIS software, PostgreSQL, and Python libraries (e.g., arcpy, gdal, pandas)
- Advanced Python skills with ability to program new scripts and modify existing scripts
- Expert in ESRI products (i.e., ArcGIS Pro, ArcEnterprise)
- Experience selecting and applying appropriate spatial and statistical analysis, as well as artificial intelligence (AI) and machine learning (ML) algorithms
- Experienced in data analysis, report development, scientific writing, and presentation of results
- Experience in communicating science to a range of audiences (e.g., academic conference, technical audience, or high-level management)
- Experience identifying, acquiring, and processing credible data (including tabular and spatial data) and metadata from online sources
- Experience collaborating on a dynamic team
- Leadership skills coordinating multiple teams and projects
Preferred Qualifications:
- Expertise with artificial intelligence (AI) and machine learning (ML) algorithms for spatial and statistical analysis
- Advanced knowledge and experience related to energy infrastructure (e.g., wells, pipelines)
- Experience developing ESRI Web Applications, including Experience Builder and Dashboards
- Experience working with energy regulator and infrastructure datasets including production and service records, such as permitting, inspection, and maintenance records
- Experience working for a U.S. national laboratory or as a research site-support contractor
Salary Range for this position is $100K to $110K
Original Posting:May 9, 2025For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.
Pay Range:Pay Range $85,150.00 - $153,925.00The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
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