Geospatial Data Scientist
- Analysis of geospatial datasets, primarily imagery, but also ground data in a variety of formats.
- Development of tools that combine spectral imagery, weather, soil, ground samples, and other datasets to determine crop physiological traits, and translation to management recommendations to growers.
- Development of machine learning models for pixel segmentation, object counting, and anomaly detection in imagery.
- Contribution to development and maintenance of existing tools related to responsibilities listed above.
- 3+ years of experience in a similar technical role
- PhD in technical field, such as Remote Sensing, Earth Science, Atmospheric Science, Physics, Computer Science
- Strong experience in a programming language used in scientific computing, such as python, MATLAB, Julia
- Experience with tools in the scientific/geospatial python stack: numpy, scipy, pandas, scikit-image, scikit-learn, geopandas, rasterio
- Experience with deep learning and neural networks, e.g., keras, tensorflow/theano
- Ability to translate prototypes into reliable and maintainable code
- Ability to iterate quickly
- Ability to clearly document work
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