Zach Cox is an associate data scientist in Spotify's User Fraud department, where he works to reduce the impact of stream manipulation (artificial streams), thus protecting royalty calculations for authentic artists and rights holders. In his previous role as A&R research analyst for Elektra Music Group, he helped to invigorate the A&R process with data and tech innovation and assisted in signing Tones and I, a global pop artist, via research analysis.
In May 2018, Cox received a bachelor’s degree from Berklee College of Music, where he double majored in music production and engineering and music business/management. In his last year at Berklee, he developed an interest in entrepreneurship, psychology, personal development, and technology. This led to a keen curiosity for data science and machine learning—specifically in regard to where technologies are headed and how they impact business and society. His exploration of data science started by learning to code in Python through various online resources. Upon graduating from Berklee, he enrolled in General Assembly’s 12-week data science boot camp, where he refined his skills to operate as a data analyst.