Research Analyst Job in Delhi at Council on Energy, Environment and Water (CEEW)

CEEW is hiring for the role of - Research Analyst (Geospatial Modelling)!

Responsibilites of the Candidate:

• Undertake geospatial modelling to support development of granular indices such as urban heat islands, mapping of green and water cover among others
• Use programming languages, primarily Python (libraries like Pandas, NumPy, Xarray), tools like ArcGIS, QGIS, Google Earth Engine, and modern systems of scientific repeatability and engineering scalability (e.g. GitHub)
• Work on big climate and geospatial data to develop granular climate risk indices
• Work extensively with CMIP5 and CMIP6-based climatological projections to derive climatic outlooks at the sub-national level through statistical methods 
• Contribute to desktop research and mining data from structured, semi-structured, and unstructured sources to develop and improve our climate risk assessments
• Working on GIS raster and vector datasets (e.g. NDVI, DEM, Elevation, hydrology network) using QGIS, ArcGIS, and Google Earth Engine derived from platforms like USGS, ESRI, et al
• Creating GIS shapefiles for analysis and preparing GIS-based maps from the extreme event and climate variability database
• Supporting the team with carrying out a literature review and research writing about climatological and spatial analysis

Requirements:

• Preferably Master’s/Bachelor’s degree in data science, climate studies, atmospheric science, GIS, environmental science, and other allied fields
• Subject domain knowledge of climate data analytics, atmospheric sciences, meteorology and geospatial technology
• Proficiency in working with big climate and geospatial data in NetCDF, raster, and vector formats
• Demonstrated ability to use the Python programming language and proficiency in using Jupyter Notebook and Python libraries like Xarray, Pandas, Geopandas and NumPy
• Proficiency in climate statistics and understanding of climatic projections derived from Global and regional climate models and their downscaling, bias correction etc
• Proficiency in ArcGIS/QGIS/Google Earth Engine
• Good knowledge of statistical tools (Excel, SPSS) and their application