Leidos Hiring for Machine Learning Geo-Scientist Job at Pittsburgh, PA Full Time

Description

Job Description:

The Leidos Research Support Team supporting the National Energy Technology Laboratory is seeking a Machine Learning Geo-Scientist to join our Team in Albany, Pittsburgh, PA or Morgantown, WV. This opportunity will allow side by side execution of research with world-class scientists and engineers using state of the art equipment to contribute to new areas of basic and applied research.

The employee will participate in studies relating to model development, workflow, and artificial intelligence/machine learning (AI/ML) algorithm design related to geospatial energy data. Additionally, the employee will be developing, managing, and integrating a variety of experimental and spatial and non-spatial datasets, including data visualization. This work will involve a multidisciplinary team participation alongside other data scientists, engineers, geologists, and computer scientists to help develop next-generation tools to understand offshore subsurface properties, hazards, oil platform infrastructure, and the priorities of the DOE Fossil Energy and Carbon Management mission space.

Location: Albany, OR; Pittsburgh, PA or Morgantown, WV

Primary Responsibilities

• Apply artificial intelligence/machine learning (AI/ML) methods to augment geospatial analysis and algorithm development
• Design a variety of supervised and unsupervised AI/ML algorithms that incorporate big, disparate, multivariate data
• Correctly and efficiently interpret AI/ML algorithm results
• 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
• Create and deliver oral, poster presentations of results
• Effectively communicate scientific results through peer-review journal manuscripts and technical reports

Required Qualifications

• Master’s degree in applied computer science, machine learning, math, spatial statistics, geography, geo-statistics, geospatial science, computational geology or similar field
• Proficiency in Python for advancing coding needs, including using Python to automate AI/ML algorithms and build data visualization tools
• Evidence of innovation in statistical methods and algorithm development as applied to geospatial statistical problems
• Demonstrable skills in the application of statistical analyses, AI/ML algorithms, and other forms of multivariate analysis
• Understanding of and experience in spatial and/or subsurface topics
• Experience using ArcGIS Server and database software management systems like Microsoft Access, SQL Server, and PostgreSQL
• Experience with GIS (ArcGIS suite), spatial mapping, and spatial analysis

Preferred Qualifications

• Advanced degree and/or certifications in data science, machine learning, applied math, computer science, spatial statistics, geology, geography, geo-statistics, geospatial science, or similar field
• Background in geospatial statistics and applications to energy and environmental systems
• Familiarity with subsurface data, including well logs and seismic, and interpretation software (Petra, Petrel, etc.)
• Familiarity with producing training datasets for image recognition and extraction from text-based resources
• Familiarity with LabelIMG, You Only Look Once (YOLO), and tensor flow
• Experience in data labeling approaches to refine and build on current classification capabilities and support AI/ML big data analysis
• Evidence of substantive participation in the geospatial and/or subsurface geologic scientific community

External Referral Bonus:

Ineligible

External Referral Bonus $:

Potential for Telework:

No

Clearance Level Required:

None

Travel:

No

Scheduled Weekly Hours:

40

Shift:

Day

Requisition Category:

Professional

Job Family:

Research Scientist

Pay Range: