<p></p><p><b>Description :</b><br/><br/>About Company :<br/><br/>We use Real Time Big Data Analysis, Digital Technology, GIS Mapping combined with Satellite/Drone Imagery, Remote Sensing and Weather Data to create innovative products.
</p><p><br/></p><p>We provide advanced technology solutions to monitor crop health, estimate crop yield, perform end-to-end digital Crop Cutting Experiments (CCEs), Smart Sampling and also use Satellite/Drone data for Crop Loss Assessment.
</p><p><br/></p><p>We are a group of young and talented agriculturists, remote sensing, GIS, Agri-insurance and IT professionals with ground-breaking ideas that we hope will contribute towards a better tomorrow.<br/><br/><b>Job Title :</b> Remote Sensing & GIS Python Developer<br/><br/><b>Location :</b> Senapati Bapat Road, Pune<br/><br/><b>About the Role :</b><br/><br/>We are looking for a skilled Remote Sensing & GIS Python Developer to design, develop, and implement algorithms for agricultural applications using remote sensing and GIS data.
</p><p><br/></p><p>The candidate will apply machine learning and deep learning techniques to extract actionable insights for agriculture, including crop monitoring and crop Classification, yield estimation, irrigation management, and land cover classification.<br/><br/><b>Key Responsibilities :</b><br/><br/>- Develop and implement Remote Sensing (RS) and GIS-based algorithms for agricultural data analysis.<br/><br/>- Preprocess, analyze, and visualize satellite and UAV imagery (Sentinel, Landsat, LISS IV, etc.) for agricultural applications.<br/><br/>- Build Machine Learning and Deep Learning models (e.g., Random Forest, XGBoost, CNN, UNet) for crop classification, disease detection, and yield prediction.<br/><br/>- Integrate GIS spatial analysis into predictive modeling and decision-making pipelines.<br/><br/>- Automate workflows for RS & GIS data processing using Python libraries like GDAL, Rasterio, Geopandas, Shapely, Earth Engine API.<br/><br/>- Work with multi-temporal and multi-spectral datasets for generating agricultural insights.<br/><br/>- Collaborate with agronomists and data scientists to validate models and improve accuracy.<br/><br/>- Optimize algorithms for scalability and high-performance computing.<br/><br/>- Prepare technical documentation, reports, and visualisations for stakeholders.<br/><br/><b>Required Skills & Qualifications :</b><br/><br/>- Strong proficiency in Python for data analysis, algorithm development, and automation.<br/><br/>- Hands-on experience in Remote Sensing and GIS using tools like QGIS, ArcGIS, and Google Earth Engine (GEE).<br/><br/>- Experience with ML/DL frameworks : TensorFlow, PyTorch, Scikit-learn, Keras, XGBoost.<br/><br/>- Knowledge of image processing, spectral indices (NDVI, EVI, SAVI), SAR, and multispectral/hyperspectral data analysis.<br/><br/>- Ability to handle vector and raster datasets, perform spatial joins, projections, buffering, and zonal statistics.<br/><br/>- Understanding of agricultural science, crop phenology, and field-level monitoring.<br/><br/>- Strong problem-solving skills, algorithmic thinking, and attention to detail.<br/><br/>- Familiarity with cloud computing and APIs for satellite data (Google Earth Engine, AWS, Sentinel Hub).<br/><br/>- Good communication skills to collaborate with multi-disciplinary teams.<br/><br/><b>Preferred Qualifications :</b><br/><br/>- M.Tech or M.Sc. in Geoinformatics, Remote Sensing, GIS, Geography Msc, Engineering, or related disciplines.<br/><br/>- Experience with field data collection and validation.<br/><br/>- Background in precision agriculture applications.<br/><br/>- Prior experience handling large-scale agricultural RS/GIS projects.<br/><br/>- Knowledge of time-series analysis for crop monitoring and seasonal variability<br/><br/></p><br/><p></p> (ref:hirist.tech)