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Andrew Yaholkovsky

Graduate StudentEmail Andrew Yaholkovsky

Andrew Yaholkovsky joins the MSiA* program at Northwestern after spending four years in a number of finance, product management, and data analytics roles, namely through the rotational leadership program at software company ServiceNow. Andrew graduated from UC Davis in 2018 with a degree in Managerial Economics with an emphasis in Finance. While studying as a third-year undergraduate, Andrew accepted a university curriculum developer position and received a grant to transition the major’s largest computing course from data analytics through Excel to predictive analytics in R. This year-long project piqued Andrew’s interest in advanced data analysis, and as such, Andrew took further courses in Econometrics, Regression Analysis, and Data Structures/Algorithms.

After graduating, Andrew joined ServiceNow’s finance rotation program and pursued rotations in Financial Planning and Analysis, Sales Operations Analytics, and Product Management. While at ServiceNow, Andrew noticed that the projects that he was most passionate about tended to be those with large datasets to which he could apply data science techniques, such as a weighted composite score metric he developed to help the Sales team predict growth by geography and by product, which eventually was used to drive headcount investment decisions. Additionally, while rotating through the Employee Experience team as a product manager, he led the product strategy, road-mapping, and go-live of ServiceNow’s “Denied Party” application which improved security by performing fuzzy string matching of all visiting parties against known domestic and foreign intelligence databases.

At Northwestern, Andrew is excited for the opportunity to learn advanced statistical methods and different analytical approaches in the classroom, and then instantly apply them to real-world data science projects through the Practicum and Capstone projects. Upon graduating, Andrew aspires to work as a data scientist for a digital/software product where he can hone his product sense and apply all he’s learned to help businesses and consumers alike make better decisions!

*later renamed MS in Machine Learning and Data Science