I’m Tala Sharif, a data scientist specializing in machine learning and systems engineering. I obtained my Master’s in Industrial and Systems Engineering at the University of Michigan. After pursuing my graduate degree, I worked as quality engineer, developing competencies in statistics, data analysis, and problem solving. I enjoy coding, mathematics, and statistics. When I’m not manipulating some cool predictive analysis, you can find me jogging, practicing kickboxing, baking, or rather indulging in chocolate.
Traditionally, an industrial and system engineer (ISE) has been viewed as the white-collar worker of a manufacturing plant, working alongside blue-collar coworkers. This understanding appropriately describes my entry-level job, to which I dedicated nearly three years of my early career. In the recent economic and technologic climate, however, the demand for increasingly unconventional roles for ISEs has increased. Currently, requirements for software and data knowledge are at their early stages of utility when plotted against the projected volume of future use. This shifting paradigm has encouraged me to adapt with the changing industry and redirect my focus on data science. I have found that my background in systems engineering has given me a solid foundation and a significant advantage with regards to the qualifications essential for a career in data science.