Project Scientist - R&D

Satelytics is seeking a self-driven, highly motivated remote sensing scientist to assist our R&D Department with expanding our software suite's geospatial analytics capabilities. The ideal candidate will be familiar with a wide range of radiometry and spectroradiometry applications and processing workflows including but not limited to: change detection, vegetation applications, hydrocarbon detection, object detection, and DSM/DTM. The duties of the position will require you to innovate new solutions to problems faced by our customers.

The Satelytics R&D team focuses on creative problem solving, developing new workflows and products, and producing robust and repeatable algorithms. As part of the R&D team, you will work independently and as part of a small group to innovate solutions using traditional and newly-developed methodologies.

Benefits
  • Paid Time off
  • 401(k)
  • 401(k) Matching
  • Dental Insurance
  • Vision Insurance
  • Health Insurance
Job Duties

  • Explore, organize, and analyze data from a variety of sources, including imagery, GIS data, and field-collected physical samples
  • Apply fundamental remote sensing principles and methods to imagery to solve client problems and challenges
  • Innovate new imagery applications independently and as part of a team
  • Generate statistically sound predictive algorithms and models
  • Script robust and repeatable algorithms
  • Report findings and recommendations to team leaders and management as new applications are developed
  • Provide remote sensing support to other teams across Satelytics and assist with projects as assigned

Requirements

  • Master’s degree in Remote Sensing, Geoscience, Geography, Statistics, Mathematics, or a related field is preferred; exceptional candidates with a Bachelor’s degree and related work experience will be considered
  • 2-4 years experience working directly with remotely sensed data

Skills

  • Practical experience in remote sensing including radiometric calibration, dimensionality reduction, classification, clustering, band-math operations, indices, and atmospheric correction
  • In-depth knowledge of multi and hyperspectral imagery
  • Familiarity with spectrometer data
  • Proven experience in applied statistics, modeling, data science, or calculus and linear algebra
  • Experience using GUI remote sensing and GIS software (e.g. QGIS, ENVI)
  • Python and/or R experience required