Research Analyst (Geospatial Modelling)

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About the Organization

The Council on Energy, Environment and Water is one of Asia’s leading not-for-profit policy research institutions. CEEW uses data, integrated analysis, and strategic outreach to explain – and change – the use, reuse, and misuse of resources.

Job Description

CEEW seeks to hire a Research Analyst skilled in geospatial modelling and data science to join the Climate Resilience team. The candidate will be supporting the team on modelling urban heat islands and other remote sensing based indices to inform India’s city heat action plans and the spatial downscaling of climate risk data as part of the Climate Resilience Atlas for India project. The Climate Resilience Atlas (CRA) is a climate risk-informed decision-making tool that will consist of various layers around climate vulnerability and variabilities. The CRA will support decision-makers in quantifying the climate risk landscape at a sub-national level.

The candidate will be required to undertake a rigorous analysis of big 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 such as Google Earth Engine and ArcGIS suite of apps, 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 Responsibilities

Research and analysis

• 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) to 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 such as downscaling, bias correction and zonal statistics.
• 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 and op-eds.
• 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.

Education Qualification/Required Skills & Experience

• Preferably Master’s/Bachelor’s degree in data science, climate studies, atmospheric science, GIS, environmental science, and other allied fields.

Work experience

• 0-3 years. Candidates in the final semesters of their Bachelor’s/Master’s 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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