Modeling Scientist

Job Summary

To enhance model traceability and uncertainty quantification, the remote Modeling Scientist will focus on improving predictive trustworthiness in ecosystem model predictions while collaborating with ecosystem modelers and data engineers.

Key responsibilities

• Generate and apply a model traceability framework for ecosystem and biogeochemical models to enable rigorous model testing and improvements
• Design and implement an uncertainty quantification framework, including parameter, structural, aleatory, and epistemic uncertainties
• Integrate machine learning techniques with process-based models to improve predictive performance and scalability

Required qualifications

• 5+ years of experience in uncertainty quantification, probabilistic modeling, and data model integration
• Advanced proficiency in Python and scientific computing, with experience building reproducible modeling pipelines
• Master's or PhD degree in Statistics, Applied Mathematics, Environmental Science, Earth System Science, Biology, or a related quantitative field
• Experience integrating machine learning with process-based or mechanistic models preferred
• Familiarity with cloud platforms and data systems, including AWS and relational or spatial databases, preferred