Senior Climate Machine Learning Scientist

MSCI•New York, NY

3d•Hybrid

About The Position

This role focuses on building physical climate risk models using advanced methodologies like AI numerical weather prediction, stochastic ensembles, earth observing foundation models, and traditional physics-based models. The scientist will collaborate with a multidisciplinary team to translate business needs into scientific solutions and design scalable scientific modeling pipelines. A key aspect of the role is maintaining scientific rigor, conducting validation studies, and staying abreast of the latest developments in machine learning, extreme weather, and climate science to enhance models and risk assessments.

Requirements

Ph.D. in Meteorology, Atmospheric Sciences, Oceanography, Hydrology, Physics, Geography, Engineering, Climate, Mathematics, or similar subjects.
2+ years of experience in roles developing products to meet client requirements.
Programming experience in Python, R, C/C++, and/or Fortran.
Experience with cloud optimized geospatial formats such as Cloud Optimized GeoTIFF (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.

Responsibilities

Build physical climate risk models using state-of-the-art methodologies including AI numerical weather prediction applied to climate applications; stochastic ensembles; earth observing foundation 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.
Architect and implement machine learning solutions for climate risk assessment.
Produce robust, reproducible models which will stand up to validation studies in a changing climate.
Follow team standards for machine learning applications to create physical risk models.
Keep up with the latest developments in machine learning, extreme weather, and climate and bring those developments to improve our models and risk assessments.
Train machine learning models written in PyTorch or JAX, then extend them for large scale inference on global scales.
Use dashboards such as mlflow, Weights and Biases, etc. to track and communicate model performance and results.
Be familiar with the latest foundation models such as Aurora, and the latest prediction models such as FourCastNet 3.

Benefits

Salary range: $102,000 - $133,000 / year.
Eligible for annual bonus.
Transparent compensation schemes and comprehensive employee benefits, tailored to your location, ensuring your financial security, health, and overall wellbeing.
Flexible working arrangements, advanced technology, and collaborative workspaces.
A culture of high performance and innovation where we experiment with new ideas and take responsibility for achieving results.
A global network of talented colleagues, who inspire, support, and share their expertise to innovate and deliver for our clients.
Global Orientation program to kickstart your journey, followed by access to our Learning@MSCI platform, AI Learning Center, LinkedIn Learning Pro and tailored learning opportunities for ongoing skills development.
Multi-directional career paths that offer professional growth and development through new challenges, internal mobility and expanded roles.
An environment that builds a sense of inclusion belonging and connection, including eight Employee Resource Groups.
Health insurance
Vision insurance
Dental insurance