Machine Learning Scientist

📋 Description

• Lead uncertainty quantification for ecosystem model predictions.
• Design probabilistic and ML approaches to quantify confidence in predictions.
• Work with modelers and data engineers to build robust uncertainty frameworks.
• Translate rigorous modeling into auditable, decision-ready outputs.
• Collaborate on model evaluation and performance metrics.
• Support monitoring, reporting, and verification platforms for emissions reductions.

🎯 Requirements

• 5+ years in uncertainty quantification, probabilistic modeling, and data model integration
• Advanced proficiency in Python and scientific computing; reproducible modeling pipelines
• Strong software engineering: modular, testable, well-documented code
• Deep commitment to scientific rigor, transparency, and integrity
• Experience integrating ML with process-based or mechanistic models (preferred)
• Familiarity with DayCent or CESM (preferred)
• Familiarity with cloud platforms and AWS and relational/spatial databases (preferred)
• Masters or PhD in Statistics, Applied Math, Environmental Science, or related field