Nir Morgulis

Nir Morgulis is currently working as a Data Science Team Leader at Similarweb. Prior to this role, they worked as a Data Scientist at the same company. Before joining Similarweb, Nir worked at HARMAN International as a Data Scientist in Automotive Cyber Security. In this role, they developed algorithms and conducted data analysis to improve automotive cybersecurity. Nir also worked on projects related to identifying cyber threats and releasing innovative algorithms. Prior to HARMAN, Nir had interned at Applied Materials as an Application Development / Algorithm Team intern. Nir conducted data analysis and optimization to improve image classification systems. Nir also served as an Application Engineer, leading implementation projects and serving as an expert in electronic microscope defect review machines. Earlier in their career, Nir worked as a Wind Energy Researcher at Tel Aviv University, focusing on improving the efficiency of wind turbines. Nir also served as a Teaching Assistant, providing instruction and tutoring in mechanical engineering courses.

Nir Morgulis obtained their Bachelor of Science (B.Sc.) degree in Mechanical Engineering from Tel Aviv University, which they completed from 2009 to 2013. Nir further pursued their education at Tel Aviv University and obtained a Master of Science (M.Sc.) degree in Mechanical Engineering from 2012 to 2014.

In addition to their formal education, Nir Morgulis has also obtained several certifications. Nir completed the "Self-Driving Car Engineer" certification from Udacity in February 2019. In October 2018, they obtained the "Feature Engineering For Machine Learning" certification from Udemy. In March 2017, they attained the "Python for Data Science and Machine Learning" certification, also from Udemy. From Coursera Course Certificates, they obtained the "Fundamentals of Digital Image and Video Processing" certificate in February 2017, the "Neural Networks for Machine Learning" certificate in December 2016, and the "Machine Learning" certificate in October 2016.