About

Chris LeBailly is a Senior Machine Learning Engineer at WhoCo with over 9 years of relevant experience in data science and data engineering. He is a lifelong learner and problem solver who is passionate about making a difference through his work. Chris is inspired by ideas and passionate people, and he loves being able to do stimulating work that combines his talents in mathematical theory along with his programming skills in a field that is constantly evolving and growing. Chris has worked with a variety of data and tools as a data scientist, including natural language processing (NLP), survival analysis, classification and clustering, and network analysis. He is proficient in using python tools such as NLTK, Gensim, spaCy, and PyTorch for NLP tasks such as text clarification, topic modeling, sentiment analysis, named entity recognition, and text similarity. Chris has also developed custom word2vec embeddings in specialized domains to improve accuracy over pre-trained embeddings. In his current role at WhoCo, Chris is working as a consultant to help clients realize the full potential of their data. He has developed a model to match members' LinkedIn, GitHub, and StackOverflow profiles, created a pip-installable package that bundles code and predictive models to deliver data science insights, and engineered a script to process matches and parallelized with Python muti-processing. Chris has also developed machinery in python to scrape websites using Docker and Selenium and parse results with lxml. He has optimized feature creation code with Numba and RapidFuzz to reduce runtime ~50x from original code, allowing processing of ~750 million records. Prior to his current role, Chris worked as a Senior Data Scientist at eye0, Inc. and Reflektive. At Reflektive, he researched how data science could augment existing product offerings in addition to building data engineering infrastructure to support analytics. Chris also developed new methodology for clustering related skills based on resume data and presented his research at hiQ Elevate conference in San Francisco and New York. Chris holds a Master's Degree in Mathematics from the University of California, Santa Cruz and a Bachelor's Degree in Mathematics and Music from Grinnell College. He is proficient in a wide range of tech stacks, including ML, Python, NLP, AWS, Data Engineering, Jupyter, Scikit, Pytorch, Apache storm, Amazon Athena, Elastic Search, ETL, Postgres, Web, and infra.