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Technical Skills

My work combines scientific depth with practical modeling. These skill areas reflect the tools and methods I use most often across climate, energy, and environmental analytics projects.

Modeling & Analytics

Statistical Modeling

88%
6+ years Regression, inference, exploratory analysis, environmental applications

Machine Learning

85%
5+ years Supervised learning, explainability, text analytics, climate applications

Agent-Based Modeling

72%
2+ years Scenario design, decision dynamics, energy transition systems

Life Cycle Assessment

70%
2+ years Integrated environmental impact assessment and trade-off analysis

Earth & Geospatial

Climate Impact Assessment

90%
6+ years Drought, environmental risk, impact pathways, adaptation questions

Remote Sensing & GIS

84%
5+ years Spatial analysis, raster workflows, environmental datasets

Hydrology & Climatology

82%
6+ years Earth system context for model development and interpretation

Scientific Computing

Python

90%
7+ years Modeling, data analysis, machine learning, reproducible workflows

R

78%
5+ years Statistical analysis, visualization, research workflows

Reproducible Research

82%
5+ years Structured analysis pipelines, notebooks, and publication-oriented work