Remote Sensing And Gis Python Developer

7 days ago

Pune, Maharashtra, India Semantic Technologies & Agritech Services Private Limited Full time ₹ 15,00,000 - ₹ 25,00,000 per year

About the Role:

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
. 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.

Key Responsibilities:

  • Develop and implement
    Remote Sensing (RS) and GIS-based algorithms
    for agricultural data analysis.
  • Preprocess, analyze, and visualize satellite and UAV imagery (Sentinel, Landsat, LISS IV, etc.) for agricultural applications.
  • Build
    Machine Learning and Deep Learning models
    (e.g., Random Forest, XGBoost, CNN, UNet) for crop classification, disease detection, and yield prediction.
  • Integrate GIS spatial analysis into predictive modeling and decision-making pipelines.
  • Automate workflows for
    RS & GIS data processing
    using Python libraries like
    GDAL, Rasterio, Geopandas, Shapely, Earth Engine API
    .
  • Work with
    multi-temporal and multi-spectral datasets
    for generating agricultural insights.
  • Collaborate with agronomists and data scientists to validate models and improve accuracy.
  • Optimize algorithms for scalability and high-performance computing.
  • Prepare technical documentation, reports, and visualizations for stakeholders.

Required Skills & Qualifications:

  • Strong proficiency in Python
    for data analysis, algorithm development, and automation.
  • Hands-on experience in
    Remote Sensing and GIS
    using tools like
    QGIS, ArcGIS, Google Earth Engine (GEE)
    .
  • Experience with
    ML/DL frameworks
    : TensorFlow, PyTorch, Scikit-learn, Keras, XGBoost.
  • Knowledge of
    image processing, spectral indices (NDVI, EVI, SAVI), SAR, multispectral/hyperspectral data analysis
    .
  • Ability to handle
    vector and raster datasets
    , perform spatial joins, projections, buffering, and zonal statistics.
  • Understanding of
    agricultural science, crop phenology, and field-level monitoring
    .
  • Strong problem-solving skills, algorithmic thinking, and attention to detail.
  • Familiarity with cloud computing and APIs for satellite data (Google Earth Engine, AWS, Sentinel Hub).
  • Good communication skills to collaborate with multi-disciplinary teams.

Preferred Qualifications

  • MTech or M.Sc. in Geoinformatics, Remote Sensing, GIS, Geography Msc, Agricultural Engineering, or related disciplines.
  • Experience with field data collection and validation.
  • Background in precision agriculture applications.
  • Prior experience handling large-scale agricultural RS/GIS projects.
  • Knowledge of time-series analysis for crop monitoring and seasonal variability.

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