Remote Sensing Analyst

Core CarbonX Solutions Pvt Ltd; Hyderabad; Remote; INR 1,200,000 - 2,500,000; Full time

Job summary

Core CarbonX is hiring a Remote Sensing Analyst to build multi-sensor time series from SAR and optical data, calibrate and harmonize across sensors, and support carbon project monitoring.

You will develop classification and change-detection models for crop types, land use, and biomass, map field boundaries, and work with field teams in agricultural settings in South and Southeast Asia. A strong portfolio and experience in Google Earth Engine, Python, and GIS tools are essential.

Qualifications

• Master's in a relevant field; Bachelor's with strong experience accepted.
• 2–6 years of hands-on remote sensing analytics, including at least 2 years in agriculture or land use
• Proven SAR experience, not only optical
• Time-series analysis with accuracy assessment against field data
• Portfolio, publications or code samples of completed projects
• Mapping agricultural fields in South and Southeast Asia
• Knowledge of rice crop calendars and water management effects on methane emissions
• Experience with field teams and farmer data collection

Responsibilities

• Build multi-sensor time series from radar (Sentinel-1) and optical imagery (Sentinel-2, Landsat, HLS, high-res data).
• Pre-process SAR and optical data: calibration, speckle filtering, cloud masking and cross-sensor harmonisation.
• Develop classification and change-detection models for crop type, tillage, irrigation, flooding regimes, land-cover change and biomass.
• Map field boundaries, run spatial analyses and measure how practices change in project areas vs baseline areas.
• Combine sensors and field data to overcome cloud cover, dense canopy, small fields and gaps between satellite passes.

Skills

Remote sensing analytics

Time-series analysis

Field data integration

Education

Master's in Remote Sensing / GIS / Geomatics / Earth Observation

Bachelor's with strong experience accepted

Tools

Google Earth Engine

Python (rasterio, geopandas, xarray, scikit-learn)

QGIS or ArcGIS

Job description

We're hiring: Remote Sensing Analyst | Core CarbonX

Want your satellite analytics to power real climate projects? Join Core CarbonX and help build the satellite-based monitoring behind our carbon projects in agriculture, forestry and land use.

Core CarbonX is a carbon trading, environmental consulting and sustainability advisory firm. We originate and implement projects that help organisations manage climate risk and build a sustainable future.

What you'll do

• Build multi-sensor time series from radar (Sentinel-1) and optical imagery (Sentinel-2, Landsat, HLS, commercial high-resolution data)
• Pre-process SAR and optical data: calibration, speckle filtering, cloud masking and cross-sensor harmonisation
• Develop classification and change-detection models for crop type, tillage, irrigation, flooding regimes, land-cover change and biomass
• Map field boundaries, run spatial analyses and measure how practices change in project areas compared with baseline areas
• Combine sensors and field data to overcome cloud cover, dense canopy, small fields and gaps between satellite passes

What we're looking for

• Master's in Remote Sensing, GIS, Geomatics, Earth Observation, Agricultural Engineering, Environmental Science or a related field (a Bachelor's with strong experience is also welcome)
• 2–6 years of hands-on remote sensing analytics, including at least 2 years in agriculture or land use
• Proven SAR experience, not only optical
• Time-series analysis and classification with accuracy assessment against field data
• Skills in Google Earth Engine, Python (rasterio, geopandas, xarray, scikit-learn) and QGIS or ArcGIS
• A portfolio, publications or code samples of completed projects
• Mapping agricultural fields in South and Southeast Asia
• Knowledge of rice crop calendars and how water management affects methane emissions
• Experience with field teams and farmer data collection

Why join us

• A central role building the monitoring backbone of real climate projects, with your methods used in registered carbon credits
• Access to commercial satellite imagery and cloud computing resources
• Competitive compensation and benefits

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