SKILLS & QUALIFICATIONS:

• Bachelor’s degree (+4 years of professional experience), Master’s degree (+2 years of professional experience), or PhD in Environmental Engineering, Environmental Science, Applied Mathematics, Geospatial Data Science,Financial Engineering, Operations Research, Computer Science, Physics, or a related engineering or quantitative field.
• Proven experience analyzing and building models using geospatial data including working with vector and raster formats.
• Strong knowledge of probability and statistical modeling, including econometric methods.
• Proficiency working with Python including common data science libraries (e.g., pandas, numpy, scipy, statsmodels), as well as geospatial data science libraries (e.g., geopandas, xarray).
• Strong analytical and problem-solving skills, with the ability to interpret complex datasets and provide actionable insights.
• Ability to work independently and collaboratively in a fast-paced, dynamic environment.
• Excellent communication and presentation skills, with the ability to convey technical information to non-technical stakeholders.
• Curiosity to continue learning about different domain and technical subjects relevant to the position.

JOB PURPOSE/BACKGROUND:

We are seeking a highly skilled, motivated, and curious individual to join our team as Quantitative Researcher with a focus on Geospatial Data Science. In this role, you will be responsible forleveraginga range of geospatial datasets, including related toweather and climate risks,to provide insights and support financial decision-making processes. You will work closely with cross-functional teams to analyze data, develop models, create visualizations, and deliver analytics that drive strategic initiatives and business growth.

KEY RESPONSIBILITIES:

• Analyze geospatial data including related to weather and climaterisks;identify trends, patterns, and anomalies; and develop models to quantify how they haveimpacted financial performance for a range of public asset classes.
• Develop, implement, and maintain models and workflows to forecast financial outcomes due to weather and climate risks, and from othergeospatial risk sources.
• Carry out necessary quality control, model governance,software development standards, and support production implementationfor successful models.
• Collaborate with cross-functional teams to integrate geospatial analytics into financial modeling, software tools, and decision-making processes.
• Create visualizations, do presentations, and writereports to communicate findings to stakeholders.
• Stay updated with the latest advancements in climate risks, geospatial data and modeling, and related financial modelingmethodologies.