Weather Data Scientist (Data Assimilation)

Ovii's Interpretation of the Role

Pravāh seeks a Weather Data Scientist to design and run data‑assimilation pipelines that feed high‑resolution forecasting models for the Indian grid. The role blends physics‑based modeling, large‑scale geospatial data handling, and machine‑learning techniques.

Role Snapshot

• Weather data scientist
• Data assimilation specialist
• Geoscience Python stack user
• HPC‑enabled pipeline builder
• Collaborates with ML and software engineers

Must-Have Requirements

• Data assimilation frameworks
• Python geoscience stack (xarray, dask, zarr, netCDF)
• High‑performance computing (HPC)
• Bias correction & QC (VarBC)
• Handling TB‑scale observational datasets
• Production‑grade pipeline development
• data assimilation
• operational forecasting pipelines
• high‑dimensional geospatial data handling
• Master’s or PhD in geophysical sciences, physics, applied mathematics, computer science, statistics, or related field
• must hold a master’s/PhD in a relevant field or a bachelor’s with 3+ years relevant experience
• onsite work in New Delhi

Nice-to-Have Signals

• Experience with Indian geography projects
• Familiarity with coupled earth‑system models
• Ensemble & probabilistic forecasting, regional downscaling, S2S prediction
• Work with operational forecasting agencies (IMD, NCMRWF, ECMWF, NOAA)
• AI‑based weather prediction techniques
• Agentic AI tools for development acceleration
• Publications in atmospheric or climate science venues
• Indian geography projects
• coupled earth‑system modeling
• AI‑based weather prediction

Work Setup

• Location: New Delhi, India
• Work mode: ONSITE
• Timezone: Evening overlap with US Pacific Time on most workdays
• Employment type: Full-Time

Not Specified in JD

• Visa sponsorship
• Salary range
• Remote eligibility
• Travel
• Security clearance
• Coding test
• Portfolio
• GitHub
• Writing sample
• Cover letter

What You'll Likely Work On

• Build and operate a cycling data‑assimilation pipeline that generates high‑resolution gridded products for operational forecasts
• Select, deploy, and customize a modern DA framework (e.g., JEDI/UFO, GSI, DART, PDAF) for regional and global needs
• Create observation quality‑control, bias‑correction, and thinning workflows that scale to TB‑size data volumes
• Contribute AI‑driven components to the assimilation workflow
• Adapt weather prediction models for renewable‑energy metrics such as solar GHI and 100 m wind
• Assist in training AI‑based weather prediction models
• Integrate physics‑based and machine‑learning approaches, including learned parameterizations and emulators

Good Fit If You Have

• Strong background in data assimilation research or operations
• Proficiency with the modern geoscience Python ecosystem
• Experience handling TB‑scale, multi‑source weather datasets