Identify, source, and conduct comprehensive reviews of datasets from multiple sources to support climate, environmental, nature/biodiversity, and regulatory datasets
Conduct comprehensive quality control reviews and validation of models, ensuring methodological rigor and accuracy in analytical outputs for research publications and client solutions
Conduct data validation and model testing to support implementation of quantitative models. These models will include climate physical risk, climate transition risk and opportunity assessment, environmental impact/emissions analysis and environmental impact valuation
Design and implement scalable data processing pipelines using Databricks
Execute data science analytical workflows for processing large-scale datasets using established statistical modeling and machine learning frameworks
Implement automation of analytical pipelines for climate, environmental, nature, and regulatory datasets following established protocols
Support presentation of research findings and recommendations to stakeholders through clear visualizations and text that communicate complex data insights effectively
What We're Looking For:
Basic Required Qualifications:
Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Environmental Science, or related quantitative field
3-5 years of experience in data science, statistical modeling, or quantitative analysis with demonstrated proficiency in programming languages such as Python, R, or SQL
Hands-on experience with big data platforms and distributed computing environments such as Databricks, Apache Spark, or similar cloud-based analytics platforms
Proven experience developing and implementing models and statistical frameworks for large-scale data processing and analysis
Strong analytical and problem-solving skills with experience in data validation, quality control, and model testing methodologies
Excellent written and verbal communication skills with ability to present complex technical findings to diverse stakeholder audiences
Additional Desired Qualifications
Experience with emissions factors development, validation, or application across various industry sectors and greenhouse gas scoping methodologies
Knowledge of input-output economic models for environmental impact assessment, including multi-regional input-output (MRIO) analysis or environmentally extended input-output modeling
Familiarity with natural capital valuation methodologies, ecosystem services assessment, or environmental accounting frameworks
Understanding of life cycle analysis (LCA) principles, including cradle-to-grave assessment, impact categories, and LCA software tools such as SimaPro, GaBi, or open LCA.
