FACTORY MUTUAL INSURANCE COMPANY Hiring! Full Time Research Scientist in West Region (Singapore), Earn up to SGD 10,000 - Ricebowl

FM is a market leader in commercial and industrial property insurance and loss prevention, providing more than one-third of FORTUNE 1000 companies with engineering/science-based risk management and property insurance solutions. FM helps clients maintain continuity in their business operations by drawing upon state-of-the-art engineering and research.

Climate risk is an identified area with increasing challenges in the next decades. To provide the best-in-class actionable science-based loss preparedness and prevention solutions to businesses, FM is making vast investments into climate research over the coming years, including the new Science and Technology Center EMEA in Luxembourg, from which the global Climate Risk and Resilience Research is being headquartered from and the expansion of the Science and Technology Center APAC in Singapore.

Join our dynamic team at the Science and Technology Center APAC in Singapore, where you will play a pivotal role in shaping the future of climate risk and resilience. As a key member of our research team, you will spearhead geospatial and AI-driven initiatives - guiding thestrategic design and deployment of scalable data pipelines, analytical workflows, and intelligent systems that transform spatial and climate data intoactionable insights for risk-informed decision-making.

We are seeking a technically exceptional scientist who thrives at the intersection of geospatial data science, artificial intelligence, and climate hazard modeling. You will contribute to high-impact research and innovation that translates into intelligent, scalable solutions for real-world risk reduction.

Responsibilities:

• Leverage, curate, and engineer cutting-edge data solutions using geospatial data sets—including geophysical data and climate hazard model outputs—to drive innovation in hazard modeling and spatial impact analysis.

• Lead the evaluation, development, and deployment of advanced AI models.

• Design and automate geospatial workflows using Python and open-source libraries to support scalable analytics.

• Translate research outputs into robust, user-aligned solutions through productization and operational integration.

• Conduct applied research on climate hazards—including tropical cyclones, floods, and extreme rainfall—while collaborating across disciplines to deliver actionable insights and shape the strategic direction of climate risk innovation in APAC and globally.

Qualified candidates must have:

• PhD in Computer Science, Geography, Environmental Engineering, or a related field.

• Fluent in Python and at least one other language (e.g., R, Fortran, Matlab).

• Strong experience in geospatial modelling, particularly in natural hazard contexts.

• Proven ability to implement and operationalize deep learning models.

• Hands-on experience with deep learning frameworks (e.g. PyTorch, TensorFlow,  JAX), with demonstrated ability to apply architecture like LSTM, U-Net, and Vision Transformers

• Proficiency with open-source geospatial tools (e.g., GDAL, rasterio, shapely, PostGIS) and GIS platforms

• Skilled in handling large datasets and automating data pipelines via scripting and APIs.

• Excellent communication skills and ability to work in high-performance, research-driven teams

Desired Skills and Competency Areas:

• Experience with HPC environments, GPU parallelization, and cloud platforms (AWS, Azure).
• Familiarity with Databricks for scalable data engineering and machine learning workflows, including Spark-based distributed processing and ML model lifecycle management.
• Familiarity with DevOps practices for scalable model deployment.
• Ability to communicate complex technical insights to non-specialist stakeholders.
• Experience in remote sensing techniques and data analysis, including satellite imagery interpretation, photogrammetry, and LiDAR processing.
• Good understanding of one or more physics-based systems and processes, particularly those related to flood dynamics, hydrometeorological extremes, tropical cyclones, and synoptic-scale weather systems