Mark Sokolov
About Mark Sokolov
Mark Sokolov is a data scientist with experience in data visualization and anomaly detection in the energy sector. He has worked at various organizations, including American Electric Power and PrivatBank, and holds a Master's degree in Computer Software Engineering from East Carolina University.
Work at American Electric Power
Mark Sokolov has been employed as a Data Scientist at American Electric Power since 2020. He operates within the Raleigh-Durham-Chapel Hill Area and focuses on utilizing data science techniques to support the energy sector. His role involves developing algorithms to track and detect anomalies in sensor data, which is crucial for maintaining operational efficiency in energy management.
Education and Expertise
Mark Sokolov holds a Bachelor of Science (B.S.) in Mathematics from North Carolina Wesleyan College, where he studied from 2014 to 2018. He furthered his education by obtaining a Master's degree in Computer Software Engineering from East Carolina University, completing his studies in 2020. His academic background equips him with a strong foundation in analytical and computational skills, essential for his work in data science.
Background in Data Science
Prior to his current position, Mark Sokolov gained valuable experience in data science through various roles. He worked as a Data Science Intern at Local Government Federal Credit Union in 2020, where he applied his skills in data analysis. He also served as a Graduate Research Assistant at East Carolina University from 2019 to 2020, contributing to research projects that utilized data science methodologies.
Experience in Tennis Coaching
Mark Sokolov has a background in tennis coaching, having worked as a Tennis Coach for the China Program in North Carolina from 2017 to 2018. He also held positions as an Assistant Tennis Professional at Carolina Country Club and as an Assistant Tennis Coach in Rocky Mount. His involvement in tennis coaching spanned several years, reflecting his diverse skill set beyond data science.
Technical Skills and Tools
Mark Sokolov is proficient in a variety of data science tools and programming languages. He utilizes Tableau for data visualization, translating complex datasets into visual formats. His technical skills include using NumPy, Pandas, Scikit-learn, Keras, and Flask for implementing time series forecasting techniques. He is also experienced in managing large datasets with SQL and noSQL databases.