MSCI is seeking a Senior Climate Machine Learning Scientist to join their team. This role involves building advanced climate risk models using cutting-edge methodologies, including AI, numerical weather prediction, stochastic ensembles, earth observing foundation models, and traditional physics-based models. The scientist will collaborate with a multidisciplinary team of climate scientists, hydrologists, fire scientists, data scientists, and data engineers to translate business needs into scientific solutions. A key aspect of the role is partnering with data, cloud, and security teams to design scalable and maintainable scientific modeling pipelines. The position also requires supporting a culture of scientific rigor and excellence in model design, including conducting validation studies for continuous improvement. The scientist will be responsible for architecting and implementing machine learning solutions for climate risk assessments, producing robust and reproducible models, and adhering to team standards for machine learning applications in physical risk modeling. Staying current with the latest developments in machine learning, extreme weather, and climate is crucial for improving models and risk assessments. The role involves training machine learning models in PyTorch or JAX, extending them for large-scale inference, and using tools like mlflow and Weights and Biases to track model performance. Familiarity with foundation models like Aurora and prediction models like FourCastNet 3 is expected.
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Job Type
Full-time
Career Level
Senior
Education Level
Ph.D. or professional degree