Are you ready to dive into the thrilling world of climate science and make a tangible impact on global resilience? Join our world-class research team, where exciting technical challenges await as we tackle the pressing issues of weather and climate risks.
We currently have a fantastic opportunity for someone to join FM Science and Technology APAC as Research Scientist – GIS Developer/Analyst for the Research Department reporting to the APAC Research Group Manager Climate Risk & Resilience.

QUALIFIED CANDIDATES MUST HAVE:

• Project and Research Management: Proven ability to manage projects and conduct research effectively
• Educational Background: MSc in Earth Sciences, Geography, or a related field.
• Experience: Practical experience in applied geospatial and/or remote sensing modelling and analysis, ideally focusing on natural hazards and risk applications.
• Data Handling: Proficient in collecting, processing, and analyzing large datasets.
• Geospatial Analysis: Thorough knowledge of geospatial analysis principles. Proficiency in quantitative analysis of both vector and raster datasets using ArcGIS and QGIS. Practical experience using open-source tools and libraries (GDAL/ OGR, rasterio, shapely, PostGIS, numpy, scipy, pandas, etc.)
• Programming Skills: Experience writing shell scripts and using APIs for process automation, excellent programming skills in at least two programming languages including Python, R, Fortran, and/or Matlab
• Communication Skills: Excellent oral and written communication and presentation skills
• Teamwork: Ability to self-start and thrive within a high-performance team environment.

DESIRED SKILLS AND COMPETENCY AREAS

• Education: PhD and a solid research record in the development and application of geospatial and/or remote sensing modelling
• Collaborative development and High-Performance Computing: Proficiency in utilizing Linux/ Unix clusters for high performance computing, along with experience in DevOps practices and cloud platforms such as AWS and Azure.
• Effectiveness in communicating highly technical and scientific insights to non-technical audiences
• Machine Learning Models: Proven experience in developing machine learning models applied to geospatial or climate data.
• Climate Science Knowledge: Understanding of meteorological and/ or hydrological processes, particularly related to tropical cyclones, synoptic-scale systems, extreme rainfall and/ or floods.

You will evaluate, develop, and implement novel techniques and models that will lead to impactful improvements in risk analytics and loss prevention for various climate perils. The ideal candidate will have a strong desire to expand research experience beyond academia and bring expertise and innovative leadership.