Junior Geospatial Data Analyst - US Only

About KatRisk

KatRisk is a leading provider of catastrophe risk modeling solutions, dedicated to helping businesses and organizations understand, manage, and mitigate the risks associated with natural disasters. Our innovative technology and expertise enable clients to make informed decisions, optimize their risk management strategies, and safeguard their assets and operations against potential catastrophes. As a rapidly growing and profitable company with strong product-market alignment, we are seeking dynamic individuals to join our team.

Role Overview

We're seeking a curious and detail-oriented Geospatial Data Analyst to join our team. In this role, you'll support client usage and development of our catastrophe risk models, while gaining exposure to various perils, geographies, and models. This is an excellent opportunity to grow your technical skills and contribute directly to impactful risk solutions.

Responsibilities

• Work with geospatial datasets for use in catastrophe risk modeling workflows.
• Assist Clients by answering support questions related to geospatial data formats, content, and usage.
• Perform quality control checks on incoming and processed data to ensure accuracy and completeness.
• Maintain clear documentation for geospatial datasets, transformation processes, and metadata.
• Convert customer-provided datasets into KatRisk's internal formats, ensuring data integrity and compatibility.
• Support model validation efforts by preparing data inputs and comparing/packaging outputs.
• Research and acquire new geospatial datasets to improve model coverage and resolution.
  
  

Requirements

Required

• MSc, MEng, or equivalent in hydrology, environmental science, geosciences, engineering, data science, or a related quantitative field.
• Quantitative skills with proficiency in R (preferred) or python for data processing and analysis.
• Experience working with large data sets including data manipulation, merging and remapping.
• Experience with geospatial data and tools (e.g., GDAL, R spatial packages, ArcGIS, QGIS).
• Detail-oriented with strong analytical and problem-solving abilities.
• Excellent communication and collaboration skills—even in remote or hybrid team settings.
  
  

Preferred

• Understanding of catastrophe modeling concepts (hazard, exposure, vulnerability, loss).
• Understanding of insurance risk metrics (AAL, PML, return periods) and probabilistic modeling concepts.
• Client facing support experience, particularly involving technical data questions or geospatial products.
• Familiar with Linux operating systems.