The first is climate and energy data: Compiling, cleaning, and verifying climate and energy datasets, such as emissions, energy production and consumption, disaster-loss, and decarbonization data; Analyzing trends across these datasets and producing visualizations and short written summaries to communicate findings; Assembling and verifying regulatory and tariff data, including retrieving primary-source documents such as utility rate schedules and reconciling them against database records. Have taken coursework, or have work experience, in energy economics, regulation, or electricity markets; Be familiar with FERC and state PUC processes, tariffs, or rate design; Demonstrate proficiency in Python and/or R, including cleaning messy or unstructured source data; Have experience building or maintaining structured datasets.