Emiliy Feldman

Emiliy Feldman has a strong background in machine learning engineering and data science. Emiliy currently works at Kayzen as a Machine Learning Engineer. Prior to that, they worked at MTS Group where they developed recommendation systems for online books and show ticket sales, improving metrics such as CTR and reading books. Before MTS Group, they were a Machine Learning Engineer at NUTSon, where they worked as a full-stack ML and data engineer, developing a recommendation system from scratch. Emiliy also has experience as a Data Scientist at United Credit Bureau, where they developed and implemented credit scoring models, and as a Machine Learning Researcher at Mindbox USA, where they developed SaaS machine learning models for marketing automation, including an original model for customer segmentation.

Emily Feldman attended Bauman Moscow State Technical University from 2014 to 2020, where they studied computer science and engineering. In addition to their degree, they obtained several certifications, including "Drawing conclusions from the data," "Mathematics and Python for Data Science," "Search for structure in data," "Supervised learning," "Diving into Python," and "Hadoop. A system for processing large amounts of data." These certifications were obtained from institutions such as Coursera and Stepik, with completion dates ranging from 2017 to 2020.