Junior (Satellite/GIS) Data Scientist

We are a leading provider of satellite/Drone data analytics and machine learning for precision agriculture. We collect data using various methods and devices, we integrate it and use machine learning to maximize the productivity of small/large farmers worldwide.

• Collect, process/transform satellite and drone datasets relevant to agriculture.
• Apply statistical analytics and/or machine learning techniques to design, code, deploy and maintain predictive models to ultimately maximize crops yields and profits.
• Create visualizations to derive insights, alerts, and recommendations for farmers.
• Model relationships between geospatial data and measurable phenomenologies.

BS or MS in science or engineering. Knowledge of satellite/drone data machine learning analytics, satellite image processing, GIS, or related disciplines is a big plus.

Programming, machine/deep learning algorithms and modeling with geospatial data 

• Software development, algorithmic scripting and modeling 
• Machine learning model development, deployment, maintenance for agricultural systems; crop phenology and agricultural life cycles, weather and impact on production

Satellite and/or drone imagery for agricultural applications, geospatial datasets 

• Satellite remote-sensing data processing (particularly Landsat, Sentinel-1&2 and MODIS) 
• Large and noisy geospatial datasets imagery and processing with GIS software
• Drone data interpretation and predictions by using machine learning and CNNs

• Google Earth Engine, experience developing Apps
• Satellite remote sensing, working with large geospatial datasets, processing satellite data for agricultural and/or weather/climate modeling
• Satellite Image processing algorithms, image sharpening, noise reduction, atmospheric corrections. GIS tools
• Strong software development and/or algorithmic scripting skills, including with AWS
• Machine Learning libraries and pipelines, Deep Learning, Convolutional Neural Networks, Computer Vision, Keras/TensorFlow, PyTorch 
• Must have designed, trained, deployed and maintained models in production
• Statistical and non-statistical methods of hyperspectral image analytics