Geospatial Data Scientist
6314 Remote/Teleworker US
Applications have closed
Leidos
Leidos is an innovation company rapidly addressing the world's most vexing challenges in national security and health. Our 47,000 employees collaborate to create smarter technology solutions for customers in these critical markets.We are seeking 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 Morgantown, WV or 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.
The successful candidate will conduct high-impact research focused on accelerating carbon management, mitigating methane emissions, characterizing and evaluating energy infrastructure, and critical minerals.
Accelerating Carbon Management – Current carbon transport and storage efforts are focused on developing federated, dynamic databases and machine learning informed, geospatial data-driven tools to inform safe injection and transport operations for CO2 across the country.
Mitigating Methane Emissions – Current methane mitigation efforts are focused on identifying and characterizing marginal, orphaned, and undocumented wellbore infrastructure through the development of national databases comprised of federal, state, and tribal resources, standardized for analysis.
Evaluating Energy Infrastructure – Current energy infrastructure integrity efforts are focused on evaluating oil and gas transport and storage infrastructure using stressors spanning the natural-engineered system (e.g., land cover, meteorological data, connected infrastructure) at a national or regional spatial scale, to inform multiple machine learning models to inform local predictions.
Critical Minerals – Current Critical Minerals efforts are focused on developing processes and technologies that enable the commercial production of critical minerals from unconventional sources in a cost effective, environmentally neutral, and sustainable way. Specifically, project goals are to identify critical mineral reserves in the US, develop and test new and advancing technologies to extract and concentrate critical minerals from these sources, use modeling and analysis to assist in rapid process optimization for technology commercialization.
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:
- Support the identification, acquisition, processing, and integration of non-spatial and spatial data using Geographic Information System (GIS) software and Python scripting.
- Provide advanced Python scripting support (i.e. develop new scripts, de-bug, expand existing scripts).
- 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 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.
- Capable of working independently to achieve day-to-day objectives.
Required Education, Experience & Other:
- Master’s degree in Geography, Environmental Sciences, Data Science, Petroleum Engineering, or related field. (PhD preferred)
- 2+ years relevant work experience programming in Python for non-spatial and spatial data acquisition, processing, and analytics.
- Proficient 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.
- Ability to travel to the NETL campuses (Albany, OR, Pittsburgh, PA and Morgantown, WV) as needed (up to 10%).
- Must be able to meet the requirements for gaining access to work on the NETL campus.
- U.S. Citizen.
Preferred Qualifications:
- Expertise with artificial intelligence (AI) and machine learning (ML) algorithms for spatial and statistical analysis.
- Experience working with energy regulator and infrastructure datasets including production and service records, such as permitting, inspection, and maintenance records.
- Advanced knowledge and experience related to energy infrastructure (e.g., wells, pipelines).
- Experience developing ESRI Web Applications, including Experience Builder and Dashboards.
- Experience working for a U.S. national laboratory or as a research site-support contractor.
Salary Range for this position: $95K to $105K
Original Posting Date:
2024-10-03While 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 $81,250.00 - $146,875.00The 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.
Tags: Data analysis Data management Engineering ETL Machine Learning ML models Pandas PhD Pipelines PostgreSQL Python Research Statistics Travel
Perks/benefits: Career development Conferences Equity / stock options
More jobs like this
Explore more career opportunities
Find even more open roles below ordered by popularity of job title or skills/products/technologies used.