Geospatial Data Scientist
1 week ago
Must Have
- Minimum 2 years of experience in Geospatial Data Science.
- Bachelor’s/Master’s degree (M.Sc./M/Tech) from an accredited College or University in Computer Science, Geoinformatics/Geomatics or related field.
- Should have experience with programming languages like Python.
- Experience in a Deep Learning framework such as Tensorflow/Keras,Pytorch.
- Strong proficiency with geospatial and imagery data
- Should have experience with Geodatabase to handle spatial data in Postgres+PostGIS.
- Proficiency in algorithm and model development, model validation, and model implementation to scale, especially with images
- Experience in handling both vector and raster data in python.
- Good communication skills, self-learning capabilities, must be a team player and self-motivated.
Role and Responsibilities
- Create innovative insights from satellite imagery and geo-location data with a focus on large scale spatio-temporal analyses, computer vision and remote sensing, feature extraction from imagery and time series data, building complex model architectures using ML/DL techniques.
- End-to-end system design: Data analysis, feature engineering, algorithm selection & implementation, debugging, and maintenance in production.
- Work with a wide range of datasets such as Raster (GeoTIFF) and Vector (Shapefile, GeoJson, KML) for data science analysis.
- Processing, cleansing, and verifying the integrity of data used for analysis.
- Creation of an automated algorithm to streamline the geospatial data processing.
- Should work on computing satellite indices for agriculture applications.
- Build/train models for agriculture applications like crop classification.
- Developing novel models for crop health monitoring and crop harvest detection.
- Suggest Data Science best practices and proper use of Code Repository and Model Repository
- Suggest optimum infra-sizing for Data Science analysis (selection of RAM, Cores, Storage)
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