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New Delhi Remote (Global) Full-time USD 20,000 – 40,000 / year

Pravāh is hiring a Weather Data Scientist (Data Assimilation)

Responsibilities

  • Develop and maintain a continuous data assimilation system to support high-resolution forecast modeling and downstream gridded output generation.
  • Select, implement, and customize a contemporary data assimilation framework such as JEDI/UFO, GSI, DART, or PDAF to meet regional and global forecasting requirements.
  • Design and manage observation preprocessing workflows, including quality control, bias correction using variational methods, and data thinning, capable of handling large-scale operational loads and partial data outages.
  • Support the creation and refinement of artificial intelligence-driven data assimilation systems.
  • Adapt numerical weather prediction models to better serve renewable energy applications, with emphasis on solar irradiance (GHI) and wind speed at turbine height (100m).
  • Help train machine learning models used in weather forecasting systems.
  • Collaborate on integrating physical models with machine learning techniques, including hybrid modeling, learned physical parameterizations, and model emulation.

Work Arrangement

Remote (Worldwide) — India, United States

About company
Pravāh

We are an AI lab building and training the foundational models to transform the electric grid. The world is changing, but the grid is not. Forecasting is getting harder due to extreme weather, electric vehicles, and rooftop solar, making demand and generation harder to predict.

Utilities lack visibility into feeder and transformer-level conditions due to outdated asset records, creating operational blind spots. Grid modeling is unreliable because utilities often operate with partial and noisy data, leading to risky decisions.

We use machine learning to give utilities a real-time understanding of how the grid behaves under stress. Our technology includes deep learning-based forecasting, graph neural networks for grid modeling, computer vision to map infrastructure, and probabilistic simulations using reinforcement learning to test thousands of possible futures.

Our solutions are deployed with utilities across India, Germany, and the United States to forecast demand, model grid constraints, and reduce operational risk in live systems.

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Job Details
Department Weather
Category data
Posted 2 months ago