Geospatial Data Scientist

2 weeks ago


New York, United States Amtex Systems Inc Full time
Job DescriptionJob DescriptionHi,Today I am working on Geospatial Data Scientist role.Required
  • Ph.D. or MS with 4+ years of post-MS experience in: Remote Sensing, Image Processing, Computer Vision, Data Science.
  • Programming: Python (Required)
  • Geospatial and machine learning libraries (TensorFlow, PyTorch (1 of these required), OpenCV).
  • Open-source tools for spatial data analysis and visualization QGIS, GDAL
  • Geospatial Data: Satellite imagery, UAV
  • Processing Geospatial Formats GeoJSON, SHP, GeoTIFF
  • Geospatial Analytics/Machine Leaning/Deep Learning Frameworks: Statistical concepts, Geo-statistics and Spatial data analysis.
  • Geospatial Image Processing with Orthorectification techniques of imageries.
  • Cloud Computing: AWS, GCP (one of these Required), Azure
  • REQUIRED to pass a non-proctored test by Filtered.AI test in Python prior to submittal
What You Will Be Doing:Join a team dedicated to solving complex agriculture problems through advanced geospatial analysis. We're seeking a highly skilled Geospatial Data Scientist with expertise in remote sensing and image processing. If you're passionate about using advanced analytics to impact agriculture and enjoy working collaboratively with scientists, IT, and engineering professionals, this role is for you.Key Responsibilities:Utilize remote sensing principles, satellite imagery analysis, and advanced image processing techniques to develop scalable image processing pipelines.Collaborate with cross-functional teams, including business stakeholders and the Data Science community, to deliver innovative solutions.Communicate complex analysis and results to key stakeholders in a clear and compelling manner.Follow data science best practices, including peer review, code review, and ensuring reproducibility.Required Skills & Experience:
  1. Education: Ph.D. in Remote Sensing, Image Processing, Computer Vision, Data Science, or equivalent; MS with 4+ years of post-MS experience is also considered.
  2. Geospatial Data: Experience with geospatial data (e.g., satellite imagery, UAV), open-source tools for spatial data analysis and visualization (e.g., QGIS, GDAL), and handling various geospatial formats (e.g., GeoJSON, SHP, GeoTIFF).
  3. Geospatial Analytics and Machine Learning: Strong understanding of machine learning/deep learning frameworks, statistical concepts, geo-statistics, and spatial data analysis. Experience with orthorectification techniques for geospatial image processing.
  4. Cloud Computing: Familiarity with cloud computing platforms (e.g., AWS, Google Cloud Platform, Azure).
  5. Programming: Proficient in Python or other high-level programming languages, with experience in geospatial and machine learning libraries (e.g., OpenCV, TensorFlow, PyTorch). Capable of writing clean code following best practices.
  6. Soft Skills: High sense of ownership, excellent communication skills, and the ability to explain technical concepts to non-experts.


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