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# Senior Climate Machine Learning Scientist

- **Company:** MSCI Inc.
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $102,000.0 - $133,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, C++ (Programming Language), Cloud Computing, Computer Programming, Fortran (Programming Language), R (Programming Language), Python (Programming Language), Machine Learning
- **Published:** October 2, 2026
- **Apply:** https://dejobs.org/x/x/969CB3A68601446EAE75E1D487B6856A/job/

## About the Role

* Ph.D.in Meteorology, Atmospheric Sciences, Oceanography, Hydrology, Physics,Geography,Engineering,Climate,Mathematics,or similar subjects.
 * 2+ years ofexperience in roles developing products to meet client requirements.
 * Programming experience in Python, R, C/C++, and/or Fortran.
 * Experience with cloudoptimizedgeospatial formats such as Cloud OptimizedGeoTIFF(COG),GeoParquet, and related standards.
 * Knowledge of the Coupled Model Intercomparison Project (CMIP) outputs and its shared socioeconomic pathways.
 * Practical experience using AI tools (i.e.Claude Code, Codex) for writing production scientific code and pipelines.

## Description

* Build physical climate risk models usingstate-of-the-artmethodologies including AI numerical weather prediction applied to climate applications; stochastic ensembles; earthobservingfoundation models; as well as traditional physics-based models.
 * Collaborate with our climate scientists, hydrologists, fire scientists, data scientists, and data engineers to translate business requirements into scientific solutions.
 * Partner with data, cloud, and security teams to design scalable and maintainable scientific modeling pipelines.
 * Support a culture of scientific rigor and excellence in model design, including conducting validation studies to guide continuous improvement of those models.

Your Key Ressponsibilities

 * Architect and implement machine learningsolutionsfor climate risk assessments.
 * Produce robust, reproducible models which will stand up to validationstudiesinachanging climate.
 * Follow teamstandards for machine learningapplications tocreatephysicalrisk models.
 * Keepup with the latest developments in machine learning,extremeweather,and climateandbring those developments to improve our models and risk assessments.
 * Train machine learning models written inPyTorchor JAX, thenextend them for large scale inferenceon global scales.
 * Use dashboards such asmlflow, Weights and Biases, etc.to track and communicatemodel performance and results.
 * Be familiar with the latest foundation models such as Aurora, and the latest prediction models such asFourCastNet3., MSCI does not accept unsolicited CVs/Resumes. Please do not forward CVs/Resumes to any MSCI employee, location, or website. MSCI is not responsible for any fees related to unsolicited CVs/Resumes.