Weather Data Scientist Data Assimilation Working hours The team is distributed across India and the US so expect a few hours of evening overlap with US Pacific Time on most workdays Overview About PravhPravh is an AI lab building foundational intelligence for the electric grid We apply modern machine learning to complex physical infrastructure problems spanning grid operations weather and geospatial systems Our work sits at the intersection of computer vision physical systems and largescale ML with deployments across utilities in the United States and India We leverage multimodal data including satellite imagery LiDAR and streetlevel data to build highfidelity representations of grid assets and their surroundings We are backed by Khosla Ventures Pear VC and Conviction some of the most ambitious investors in Silicon Valley More about who we are what we are building and why we are excited Website Pravh on Notion The roleWe are hiring a Weather Data Scientist to advance the next generation of weather forecasting systems for India with strong attention to observational data quality and geospatial consistency You will work closely with machine learning and software engineers on three core threads 1 Data assimilation contribute handson to data assimilation for weather forecasting models 2 MLready datasets procure process and create MLready global and regional weather datasets at large scale high volume multisource long time horizons with explicit focus on datasparse regions What youll work on Build and operate a cycling data assimilation pipeline for our operational forecasting models and produce the highresolution gridded products it enables downstream Choose deploy and adapt a modern DA framework e g JEDI UFO GSI DART PDAF for our regional and global needs Develop observation quality control bias correction VarBC and thinning workflows that hold up at operational data volumes and degrade gracefully when feeds drop out Contribute to AIbased data assimilation pipelines Tailor weather prediction models to renewablesector needs particularly solar GHI and wind generation 100m winds Assist in training AIbased weather prediction models Work at the intersection of physicsbased modeling and machine learninghybrid physicsML systems learned parameterizations and emulators Who you areRequired qualifications A masters or PhD in geophysical sciences physics applied mathematics computer science statistics or a related field A bachelors degree with 3 years of relevant research or operational experience is also acceptable Demonstrated depth in data assimilation evidenced by operational work model contributions research projects publications or technical reports Handson experience across the DA toolkit observation operators and error specification variational 3D 4DVar or ensemble EnKF LETKF EDA methods cycling workflows and innovation statistics and assimilation of satellite radar radiosonde or station observations Handson experience with at least one operational DA framework JEDI UFO GSI DART PDAF or an inhouse equivalent including building observation operators and forward models Working knowledge of bias correction VarBC adaptive QC and grosserror rejection Experience contributing to or maintaining assimilation code or holding responsibility in an operational or quasioperational forecasting pipeline Experience working with TBscale highdimensional observational and modeling datasets reanalysis satellite radar weatherstation and sounding data and the geospatial pipework grids reprojection masks around them Handson experience with widely used reference datasets such as ERA5 MERRA2 IMDAA IMERG GPM and GOES INSAT Himawari Practical experience on High Performance Computers HPCs Fluency in the contemporary geoscience Python stackxarray dask zarr netCDF Experience building reproducible productiongrade pipelines Excellent written and verbal communication including the ability to explain technical work to both domain experts and crossdisciplinary collaborators Nice to have Prior work on projects specific to Indian geography Familiarity with coupled earthsystem models Experience with any of ensemble and probabilistic forecasting regional downscaling or subseasonaltoseasonal S2S prediction Experience working with operational forecasting agencies IMD NCMRWF ECMWF NOAA etc Familiarity with AIbased weather prediction models and data assimilation techniques Comfort using agentic AI tools to accelerate development Publications in respected atmospheric oceanic or climate science venues What youll Weath

📌 Weather Data Scientist Data Assimilation (Delhi)
🏢 Pravh
📍 Delhi