Oleksandr Nazarenko

Head Of Fraud Protection, Product Manager at MGID Inc.

Oleksandr Nazarenko has a diverse work experience spanning multiple industries and roles. Their most recent position is at MGID, where they serve as the Head of Fraud Protection and Product Manager. Prior to that, they worked at TechExpert, starting as the Head of Digital Marketing/Digital Transformation Department and then transitioning to the role of Head of BI Department. Before TechExpert, they held the position of Chief Marketing Officer at Tucha Cloud Solutions Provider. Oleksandr also has experience as the Head of the Training Center at ERC, Production Editor at KP Media, and various roles at Dialektika Computer Publishing, including Head of the Economic Literature Department and Translator/Editor. Overall, Oleksandr's work experience showcases their expertise in fields such as fraud protection, digital marketing, business intelligence, and cloud solutions.

Oleksandr Nazarenko obtained a Master's degree in Theoretical and Mathematical Physics from Taras Shevchenko National University of Kyiv, completing their studies from 1996 to 2001. Oleksandr has also obtained various certifications, including a Certified SAFe 5 Agilist certification from Scaled Agile, Inc. in April 2021. Oleksandr has additional certifications in AWS Fundamentals, Statistics with Python Specialization, TensorFlow: Data and Deployment Specialization, Convolutional Neural Networks in TensorFlow, Deep Learning Specialization, DeepLearning.AI TensorFlow Developer Specialization, Natural Language Processing in TensorFlow, Sequence Models, Convolutional Neural Networks, Improving Deep Neural Networks: Hyperparameter tuning, Regularization, and Optimization, Neural Networks and Deep Learning, Business Analytics for Decision Making, Business Applications of Hypothesis Testing and Confidence Interval Estimation, Data for Machine Learning, Databases and SQL for Data Science, Decision-Making and Scenarios, Introduction to Data Science in Python, Machine Learning, and Machine Learning Algorithms: Supervised Learning Tip to Tail, acquired from various institutions in the past.

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