William Lane

William Lane has a diverse work experience in various roles and companies. William started their career as a Data Science Fellow at Bayes Impact, where they developed a fraud detection algorithm for a microlending non-profit. William then worked as a Data Scientist at Cognito, analyzing gameplay data and designing game performance screens. William later joined Google as a Data Science Engineer, where they worked on designing databases and dashboards for the Logs team, as well as leveraging data for product decisions in the Google Search App for iOS. William also worked as a Quantitative Analyst at Google, responsible for designing A/B tests, building dashboards, and data pipelining. William then joined Curology as a Data Engineer, Platforms, involved in developing data infrastructure and designing data pipelines. At Apple, they worked as a Data Scientist, counting sign-ups for marketing promotions and creating interactive dashboards. William'smost recent role was as a Research Data Scientist at Nightingale Open Science, where they assembled a collection of EHR and medical image data and implemented machine learning algorithms for ECG and X-ray data. Currently, William is working as a Software Engineer at Arine, where they are writing a library for accelerating customer onboarding and establishing data standards.

William Lane's education history includes a Master of Science (MS) in Statistics from Stanford University, a Master of Arts (MA) in Economics from North Carolina State University, a Bachelor's Degree in East Asian Languages, Literatures, and Cultures from Columbia University, and a High School Diploma from Asheville School. In addition to their formal education, William Lane has obtained several certifications, including "Learn Rust Building Real Applications" from Udemy, "Google Cloud Platform Big Data and Machine Learning Fundamentals" from Coursera, "Triplebyte Certified Generalist Software Engineer" from Triplebyte, "Introduction to Big Data" from Coursera, "Neural Networks and Deep Learning" from Coursera, and "Algorithms and Data Structures: Algorithmic Toolbox" from Coursera.