Radion Bikmukhamedov

Radion Bikmukhamedov began their work experience in 2014 as an IT Specialist at DataExpress, where they focused on deploying and maintaining switching and routing devices on enterprise networks. In 2017, they joined TMT LLC as an Engineer before becoming the Lead Engineer in 2018, and their responsibilities in both roles are not provided.

Beginning in 2016, Bikmukhamedov worked as a PhD Student at Kazan National Research Technical University. There, they focused on various projects involving mobile networks, machine learning algorithms for network traffic classification, and statistical network traffic modeling.

In 2019, they joined Factory5.ai as a Machine Learning Engineer. In this position, they were involved in two main projects: a news monitoring project where they handled end-to-end design and development of ML components, and a chat-bot project where they contributed to the bot's core and designed and developed text classification and named entity recognition services.

In 2020, Bikmukhamedov became a Data Scientist at ANNA Money. Radion'sresponsibilities included ad-hoc data analysis, automating compliance processes using machine learning, and unifying and engineering the ML stack and pipeline for the DS team.

Overall, Radion Bikmukhamedov has a diverse background in IT, machine learning, and data science, with experience in various roles and responsibilities.

Radion Bikmukhamedov completed their Bachelor's degree in Telecommunications Engineering from Donetsk National Technical University from 2010 to 2014. Radion then pursued two Master's degrees concurrently, earning one in Telecommunications Engineering from Kazan National Research Technical University named after A.N.Tupolev – KAI from 2014 to 2016, and another in Communications and Signal Processing from Technische Universität Ilmenau during the same period. In terms of additional certifications, they obtained a CCNA SP (Cisco Certified Network Associate Service Provider) certification from Cisco in December 2017 and a certification in Machine Learning Engineering for Production (MLOps) from DeepLearning.AI on Coursera in January 2022.