About me
Biologist and data scientist with 15+ years of experience in quantitative research in environmental science, sustainability, transportation, and land use. Strong interest in integrating multiple data sources to generate novel insights for applied research. Deep knowledge of statistical and machine learning tools for analyzing complex data sets and creating compelling visualizations. Strong communication skills, with extensive peer-reviewed publications and lecturing experience.
Tools I use
Every day
Data wrangling, visualization, and statistical modeling is my everyday work. This modeling work can include mixed-effect models, time-series analysis, multivariate analyses (ordination, classification, and clustering), structural equation modeling, analysis of experimental and observational data, and machine learning. For these I use:
- R + RStudio + rmarkdown
- git + GitHub
- Python in PyCharm or Jupyter Notebooks
Proficiency for specific jobs
Some projects require spatial modeling, latent variable modeling, hierarchical Bayesian approaches. Visualization tools needed may be interactive, web-hosted, or simply nicely-formatted graphics in a publishable PDF. There’s a large number of tools I use for these types of tasks, including:
- ArcGIS, arcpy, spatial data analysis packages in R
- Stan for Bayesian modeling
- Tableau, Plot.ly, Shiny for visualization
- JavaScript, CSS, HTML, server management
- Shell scripts, .bat files
- LaTeX, bibtex
- Amazon Web Services, Azure for cloud computing
- Databricks, Spark, Hive/Hadoop
Things I’ve written
- Author or co-author on over 40 peer-reviewed publications. Previously acted as an Associate Editor for Journal of Ecology and Journal of Plant Ecology, and reviewer for over 20 journals, including Transportation Research Record, Biogeosciences, Global Ecology and Biogeography, Nature Communications, Ecology Letters, Food Policy, and Proceedings of the National Academy of Sciences.
- Extensive experience synthesizing information about highly technical topics for the general audience, particularly in the fields of ecology, environmental sciences, and global change science.
- Knowledgeable on topics related to climate, transportation, land use change, energy, and sustainability.