Unlock Premium Perks

Get Immediate Access to 2,714,000 premium jobs

- Direct Access to Top Employers

Gain full access to exclusive job listings from leading companies worldwide.

- Verified, High-Quality Jobs Only

No ads, scams, or junk-just genuine opportunities.

- Focus on Real Opportunities

Explore thousands of open positions tailored to your lifestyle, including flexible remote jobs.

- Exclusive Resume Review

Receive expert feedback with personalized suggestions to enhance your resume.

Continue →

Job Summary

Python Developer / Data Scientist for ADS

Geospatial

- Strong with the Python geospatial stack: GeoPandas, Shapely, Rasterio, pyproj, Fiona
- Solid grasp of coordinate reference systems (CRS), projections, and reprojection pitfalls
- Vector and raster handling: polygons, field boundaries, GeoTIFFs, zonal statistics, clipping, masking, resampling
- Spatial joins, overlays, and intersection logic at scale (e.g., field polygon vs.



land-cover raster)
- Familiarity with common formats: GeoJSON, Shapefile, GeoPackage, Cloud-Optimized GeoTIFF (COG), Parquet/GeoParquet

Key Responsibilities

Agro domain

- Understanding of crop types, growing seasons and crop calendars
- Knowledge of key agronomic risk drivers: drought, flood, frost, heat stress, hail, pests/disease
- Familiarity with agricultural data sources: land-cover and crop-type products (e.g., MapBiomas), yield statistics, soil data
- Ability to translate agronomic concepts into data features (e.g., NDVI anomalies, precipitation deficits, growing degree days)

Skill Requirements

Python and data science core

- Production-quality Python: clean, tested, typed, maintainable code.
- SQL, ideally PostgreSQL

Other Requirements

📌 Senior MLOps Technical Lead (India)
🏢 HCL Technologies
📍 India