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Data scientist • brockton ma
Research Scientist - Weather and Climate Risks
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Overview
Join our dynamic research team at the forefront of climate science. As a Research Scientist, you will lead pioneering investigations into extreme weather phenomena and their evolving risks. Your initial focus will be on modeling tropical cyclones, severe convective storms, and intense precipitation events. Additionally, you'll contribute to regional initiatives and collaborate with global colleagues to advance our Climate Risk & Resilience program.
Key Responsibilities
Design and execute innovative research projects targeting extreme weather events.
Create and apply advanced modeling techniques to improve risk assessments and loss mitigation strategies.
Collaborate with international research teams based in the ., Singapore, and Luxembourg.
Support the development of hazard models for flood, wind, storm, and wildfire risks.
Minimum Qualifications
Option 1 : MS in meteorology, data science, or a closely related field, with 3+ years of applied experience modeling extreme weather.
Option 2 : PhD in meteorology, data science, or a related discipline, with demonstrated expertise in statistical / dynamical downscaling.
Core Skills & Competencies
Project Management : Track record of leading research initiatives from concept to execution.
Data Mastery : Skilled in handling large datasets with precision and efficiency.
Statistical Expertise : Experience with extreme value theory and probabilistic analysis.
Machine Learning & AI : Proficient in building ML models for climate and geospatial data, including neural networks.
Climate Science : In-depth understanding of atmospheric processes linked to major weather systems.
Modeling & Simulation : Hands-on experience with climate models (global / regional), CMIP6 datasets, and multi-format data integration.
Programming : Advanced skills in Python, R, Fortran, Matlab, shell scripting, and API integration.
Communication : Strong written and verbal skills; capable of presenting scientific insights clearly.
Teamwork : Self-motivated and effective in collaborative, performance-driven environments.
Preferred Qualifications
PhD with a robust publication record in atmospheric / climate science.
Experience with HPC in Linux / Unix environments, cloud computing (AWS, Azure), and DevOps practices.
Ability to simplify complex findings for non-specialist stakeholders.
GIS proficiency (ArcGIS, QGIS, GDAL, Google Earth Engine).
Stochastic modeling experience for simulating natural hazards.