Arva Intelligence - Modeling Scientist

• Uncertainty Quantification and Model Evaluation • Generate and apply model traceability framework for ecosystem and biogeochemical models to enable rigorous model testing and improvements • Design and implement uncertainty quantification framework for the models, including parameter, structural, aleatory, and epistemic uncertainties • Quantify and communicate model confidence, uncertainty bounds, and performance metrics • Statistical and Probabilistic Modeling • Develop hierarchical and Bayesian approaches to support distributed and iterative model optimization • Analyze model outputs to diagnose limitations and inform model improvement strategies • Machine Learning and Model Integration • Integrate machine learning techniques with process-based or mechanistic models to improve predictive performance and scalability • Partner with data engineers to implement reproducible, scalable modeling pipelines • Contribute to the design of model evaluation and optimization workflows • Scientific Communication and Documentation • Communicate uncertainty, confidence intervals, and model performance clearly to internal teams and external stakeholders • Contribute to scientific reports, transparent model documentation, and peer-reviewed publications as appropriate • Support defensible, auditable model outputs suitable for regulatory and credit market review • 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. • Quantify and communicate model confidence, uncertainty bounds, and performance metrics. • Develop hierarchical and Bayesian approaches for distributed and iterative model optimization. • Analyze model outputs to diagnose limitations and inform model improvement strategies. • Integrate machine learning techniques with process-based models to improve predictive performance. • Partner with data engineers to implement reproducible, scalable modeling pipelines. • Contribute to the design of model evaluation and optimization workflows. • Communicate uncertainty, confidence intervals, and model performance clearly to stakeholders. • Contribute to scientific reports, model documentation, and peer-reviewed publications. • Support defensible, auditable model outputs for regulatory and credit market review. • Employment Eligibility • Only applicants currently, and in the future, eligible to work in the United States will be considered for this position. • Summary: The Modeling Scientist is responsible for enhancing model traceability, uncertainty quantification, and predictive trustworthiness within Arva's ecosystem model predictions. This role is pivotal in advancing Arva’s platform for monitoring, reporting, and verifying greenhouse gas emission reductions and removals. Collaborating at the intersection of statistics, machine learning, and process-based ecosystem modeling, the Modeling Scientist ensures robust model traceability and uncertainty frameworks, delivering transparent, decision-ready outcomes for customers, partners, and environmental markets.