Nan(Lainey) is a master student at New York University studying Financial Engineering. She is passionate in the applications of machine learning technique in financial industry eg. High-Frequency Trading, Option Pricing. Nan developed a shiny app to research on Momentum Trading and Replicating Option Strategy, and she scraped IMDB and Wikipedia to analyze original contents produced by Netflix, Hulu, and Amazon. She collaborates with three group members on Kaggle Competition: predicting housing price. For the Capstone project in NYCDSA, her team implemented machine learning to match mentors and mentees from BuiltByGirls. She also has past experiences with economic research, trading, financial statement, and public speaking. Nan passed both CFA level 1 and Series 57 in 2016. Linkedin: https://www.linkedin.com/in/nankeddell/
In the fast-paced world of data science, you need a little more than technical skills to transition from being a student to being hired.