Consultant - Climate Data Specialist

• Frequency analysis of extreme climate events (e.g., extreme rainfall, IDF curves)
• Conducting climate-related vulnerability and risk assessments
• Quantifying and correcting for statistical bias in climate datasets

• Experience with climate change models and data portals, preferably with demonstrated experience in statistical and dynamical downscaling
• Employment with WSP India is subject to the successful completion of a background verification (“BGV”) check conducted by a third-party agency appointed by WSP India.
• Experience routinely working on coding projects and adapting scripts and programs written by colleagues, enhanced by a strong aptitude in standard programming practices.
• Strong statistics background, preferably with demonstrated experience in statistical methods for meteorological data infilling and trend analysis
• Experience working with tools and/or coding scripts for effective data processing, analysis, and visualization.
• Proficiency in version control systems (e.g., Git, GitHub) for managing code and collaborating on projects
• Experience working independently and on efforts requiring remote collaboration.
• Undergraduate or graduate degree in data science, hydrology, meteorology, atmospheric science, climate science, environmental engineering or a related field
• Attention to detail; commitment and skills to identify and detect errors; commitment to thorough quality reviews and checks; and commitment to accuracy, correctness, and excellence.
• Experience with high-performance computing (HPC) and parallel processing in cloud environments (e.g., AWS, Google Cloud, Azure).
• Hazard modeling approaches that use climate data as inputs (e.g., hydrologic modeling, flood and storm surge modeling, wildfire modeling).
• Ability to innovate on challenging topics to produce client-tailored products.
• Preferable candidates will understand:

Frequency analysis of extreme climate events (e.g., extreme rainfall, IDF curves)

Quantifying and correcting for statistical bias in climate datasets

Hazard modeling approaches that use climate data as inputs (e.g., hydrologic modeling, flood and storm surge modeling, wildfire modeling).

Conducting climate-related vulnerability and risk assessments

• Experience communicating orally and in writing technical analysis and results to non-technical audiences using data visualization and maps.
• Must have strong computer skills including programming skills (e.g., Python) and data management and processing skills related to model output (e.g., familiarity with NETCDF file formats)