I use computational approaches to answering ecological questions about the commonness and rarity of species across space and time. My primary programming language is Python, but I have used R a little, and am working to become more fluent.
This is a fancy word for what I like to call "data wrangling". This involves compiling data from the literature into new databases, as well as working with pre-existing data and databases to clean, extract, and do new exciting things with the data. I compiled or helped to compile two databases as a PhD student (see my Research Products) and have contributed several scripts to the EcoData Retriever, an open source tool developed by the Weecology group to do the work of processing publicly available datasets.
As an unaffiliated computational ecologist using large, publicly available ecological datasets, I am a strong advocate of open science, and I try to keep my work as open as possible. Current and past research projects and products are publicly available on GitHub and figshare. I firmly believe that making science more open and reproducible not only improves the pace and ultimate quality of the scientific process, but it also makes science more accessible to under-represented groups (like sick, homebound ecologists) that would not otherwise be able to participate in the scientific process.