Job Description

The candidate will be required to undertake a rigorous analysis of big climate and geospatial data to develop climate risk indices and support the core research team primarily with data mining, data analysis, and literature review. The ideal candidate must have an educational background in data science, GIS, Climate studies, Atmospheric sciences, Environmental science, and other allied fields and should have working experience with programming languages such as Python, GIS tools, Microsoft Office and other statistical tools. Knowledge of machine learning and deep learning would be an added advantage. In addition to the duties and responsibilities below, the individual should be prepared, as and when necessary, to take on additional responsibilities. Job duties and accountabilities Primary responsibilities Research and analysis 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) to work on big climate and geospatial data to develop granular climate risk indices. Support the core team with working on CMIP5 and CMIP6-based climatological projections to derive climatic outlooks at the sub-national level through statistical methods such as downscaling, bias correction and zonal statistics. Support in updating CEEWs existing research based on IPCC frameworks for vulnerability and risk assessments to the latest frameworks in risk assessments. 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. Other responsibilities Support the team and build individual capacity in strategic communications through regular blogs. Respond to research requests from senior researchers, discuss research needs, and prepare responses that synthesize and analyze information. Assist with program implementation, including help with preparing presentations. Assist with planning and executing events such as report launches, consultation workshops, round table discussions, etc. Participate constructively in weekly team meetings. Provide inputs on research methodology and data analysis tools. Selection Criteria Qualification Preferably Masters/Bachelors degree in data science, climate studies, atmospheric science, GIS, environmental science, and other allied fields. Candidates pursuing their degrees can also apply. Work experience 0-1 years. Candidates pursuing their Bachelors/Masters can apply. Key skills 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 applications. Demonstrated ability to perform a literature review.

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