Cangyuan Li

I am a Research Scientist at NYU with a strong background in programming. I regularly use Python (primarily Pandas and Numpy), R, and Stata for a wide range of applications, from small utility scripts to large-scale data collection and analysis. For example, as part of a project to study racial biases in lending, I wrote an object-oriented Python library to scrape LinkedIn. The library was able to sufficiently mimic human typing and movement to bypass the site’s bot detection, search for profiles based on name and company, and collect information such as education and work experience. Furthermore, working with very large data (frequently over 8 million rows) has sharpened my eye for algorithmic complexity, profiling, and optimization. I am comfortable with identifying “hot paths” to balance both development and processor speed, and with applying techniques such as multithreading, loop unrolling, vectorization, and more efficient data structures to address the pinpointed inefficiencies. Relatedly, I also am familiar with cloud computing and remote development. I am comfortable using the terminal, Bash, SSH, job schedulers such as Slurm, and navigating Windows and Unix-based servers. I also have experience setting up AWS instances for Python development. Finally, working on projects with multiple contributors has sharpened my ability to synthesize and communicate information clearly and succinctly, particularly in code. In a fast-paced environment, it is easy to write things in an esoteric manner. In order to collaborate effectively, I am constantly improving my ability to write clean, understandable, flexible, and scalable code.