Shaked Erenfeld
About Shaked Erenfeld
Shaked Erenfeld is a Data Scientist at ControlUp in Israel, where he has worked since 2018. He specializes in designing algorithms and predictive models to enhance business revenue and has a strong academic background in Neuroscience from Bar-Ilan University.
Work at ControlUp
Shaked Erenfeld has been employed as a Data Scientist at ControlUp since 2018. In this role, he has designed and implemented custom algorithms and predictive models aimed at enhancing business revenue and customer value. He has focused on measuring and improving global benchmarks through data analysis. Erenfeld achieved second place in a company-wide hackathon, showcasing his skills in innovative problem-solving. He has also developed latent fault detection in large-scale services, contributing to the company's operational efficiency.
Education and Expertise
Shaked Erenfeld studied at Bar-Ilan University, where he earned a Bachelor of Science (B.Sc.) in Neuroscience from 2013 to 2015, followed by a Master of Science (M.Sc.) in Neuroscience from 2015 to 2017. His academic background provides a strong foundation for his work in data science, particularly in the application of analytical techniques to complex problems. Erenfeld has expertise in developing predictive models, including the implementation of the predictive time series model 'Prophet' developed by Facebook.
Background
Before joining ControlUp, Shaked Erenfeld worked as a Research Assistant at Bar-Ilan University from 2013 to 2018. This five-year experience allowed him to gain valuable insights into research methodologies and data analysis. His work during this period contributed to his understanding of data-driven decision-making, which he applies in his current role as a Data Scientist.
Achievements
Shaked Erenfeld has made significant contributions to his field, including achieving second place in a company-wide hackathon at ControlUp. He has developed custom data solutions tailored for enterprise clients, demonstrating his ability to address specific business needs through data analysis. His work on latent fault detection in large-scale services is based on research from Technion, further highlighting his commitment to advancing data science applications.