Roman Shaptala

Roman Shaptala has worked as a Machine Learning Engineer at Proxet since January 2019, where they have contributed to projects such as Carmen, Employa, and Mango. In these projects, they have designed and implemented a graph embeddings-based solution for skills synonymy, developed models and services for resume parsing and named entities normalization, and researched and deployed subpixel super-resolution algorithms for images in the microbiological domain.

In addition to their work at Proxet, Roman also has experience as a Teaching Assistant at the National Technical University of Ukraine 'Kyiv Polytechnic Institute' from September 2019 to July 2021, where they designed and taught an "Introduction to Machine Learning" course, as well as assisted in teaching other subjects.

Prior to their current role, Roman was an Intern at IBM from July 2017 to October 2017, and a Data Scientist at SoftIndex from November 2015 to May 2017.

Roman Shaptala pursued their education in computer science. Roman completed their Bachelor's Degree from the National Technical University of Ukraine 'Kyiv Polytechnic Institute' in 2016. Following that, they obtained a Master's Degree in Computer Science from the same university, which they completed in 2018. Alongside their formal education, Roman also obtained various certifications, including "Palantir Foundry Foundations" from Palantir Technologies in March 2023, "Google Project Management: Specialization" from Coursera in September 2022, and numerous others from institutions like DataCamp, Coursera, and Educative, Inc. Roman'scertifications span topics such as data privacy, machine learning engineering, database design, and AWS S3. Roman's dedication to continuous learning is apparent from their varied educational pursuits.