Weather Scientist (New Delhi)

Weather Scientist (New Delhi)

04 Sep
|
Pravah
|
New Delhi

04 Sep

Pravah

New Delhi

About Pravāh
Pravah is building the world's first foundation model of the electric grid. The world's most important physical industry is under unprecedented stress. We are using ML to build the 22nd-century grid. We are backed by Khosla Ventures, Pear VC, and Conviction.

We work directly with state-owned distribution and transmission electricity utilities to transform their decades of fragmented operational data into deployable, decision-grade intelligence. Our customers include some of the largest DISCOMs in the country, and our work spans demand forecasting (including renewable generation forecasting), weather forecasting, network mapping, and load flow analysis.

The role
We are hiring a Weather Data Scientist to advance the next generation of weather forecasting systems for India, with robust attention to observational data quality and geospatial consistency. You will work closely with machine learning and software engineers on two core threads:
- Numerical weather prediction: run regional NWP models to generate high-resolution forecasts and training data.
- Data assimilation:



contribute hands-on to data assimilation for weather forecasting models.
- ML-ready datasets: procure, process, and create ML-ready global and regional weather datasets at large scale (high volume, multi-source, long time horizons), with explicit focus on data-sparse regions.

What you'll work on
- Build and benchmark next-generation multiscale, regional, and global forecasting systems against reanalysis and observations, with particular focus on nowcasting and extreme events. The work rests on careful treatment of station, radar, satellite, and other observational data, and on geospatial alignment to model grids.
- Build and operate a cycling data assimilation pipeline for our operational forecasting models, and produce the high-resolution gridded products it enables downstream.
- Develop observation quality control, bias correction (VarBC), and thinning workflows that hold up at operati

📌 Weather Scientist (New Delhi)
🏢 Pravah
📍 New Delhi

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