Department of Mathematical and Statistical Science alumnus Logan Ewanchuk. Photo supplied.
The journey from classroom to career can take many forms. For alumnus Logan Ewanchuk, his career in risk analysis grew from his master’s studies research—and an internship opportunity that led to working for Canadian Western Bank (CWB).
As a model validation risk analyst, his job includes completing backtesting and validation reports related to risk models, helping understand—and verify—the calculation of risk. It’s a career that came naturally to Ewanchuk, as he explains his interest in quantitative subjects, and harnessing that interest in the Department of Mathematical and Statistical Sciences.
“It is clear that in this technologically driven world, data has become a key resource in the majority of professional settings,” said Ewanchuk. “Of course, assessing risk quantitatively requires considerable knowledge in mathematics and statistics, and this is not limited to financial mathematics. Simple decision making, on a daily basis, relates to math more than you would typically think, so it is useful to think of math as your friend.”
Hear from Logan on selecting UAlberta for his studies, how research and a work-integrated learning opportunity turned into a career, and how math can be applied in more places than students might first think.
What led you to select the University of Alberta’s Department of Mathematical and Statistical Sciences for your studies?
The University of Alberta is a prestigious academic institution, and is reasonably close to home for me. Additionally, I was confident in the Department of Mathematical and Statistical Sciences, both in terms of the quality of teaching and the opportunity for meaningful research. I have always been interested in quantitative subjects, and have a passion for extracting interesting, objective conclusions from data or any numerical information. In my opinion, the eventual interpretation of numerical results is even more important than the initial analysis, as context and explanation are key to effective communication of statistical findings.
Your master’s studies included a research project and an internship opportunity. Tell us about your studies.
Chris Frei, associate professor in the Department of Mathematical and Statistical Sciences, was my thesis supervisor for my master's studies. While my degree was officially in statistics, my research heavily focused on financial topics—namely, credit risk management.
During the second year of my master’s studies, Frei arranged an internship opportunity for me at Canadian Western Bank (CWB) as part of a research collaboration funded by the Natural Sciences and Engineering Research Council of Canada (NSERC). Specifically, I was able to take an intern position on the model validation team at CWB. This experience allowed me to continue to build my understanding of quantitative finance and credit risk management, as well as gain familiarity with the practical objectives of the model risk departments at the bank. It was a unique chance to apply the theoretical ideas reflected in my thesis project in a specifically relevant practical setting.
Tell us about your career as a risk analyst with CWB.
As a model validation risk analyst, I am responsible for completing backtesting and validation reports related to applicable risk models. This involves preparing data appropriately for backtesting and validation purposes, using knowledge of CWB data systems. Additionally, comprehensive understanding of various credit risk models is required. I also have the opportunity to communicate with senior risk leaders at CWB regarding important objectives and analyses during critical projects in our department.
Ultimately, an exciting aspect of this job is that it is not predictable or monotonous in terms of daily work. Thus, the general problem-solving skills developed during academic studies are of utmost importance. Data analysis, programming skills, as well as theoretical knowledge of credit risk models are all significant, although I would say that the ability to find solutions to newly emerging problems, through critical thinking, is important in any rewarding career.
From your perspective, why is it important to study mathematical & statistical sciences?
It is clear that in this technologically driven world, data has become a key resource in the majority of professional settings. Of course, assessing risk quantitatively requires considerable knowledge in mathematics and statistics, and this is not limited to financial mathematics. Epidemiology, economics, and business studies are just a few prime examples of fields where statistical analysis plays a prominent role.
Although advanced mathematics and statistics are of course interesting to myself and many others, basic quantitative skills need to be mastered regardless of a person’s career. Simple decision making, on a daily basis, relates to math more than you would typically think, so it is useful to think of math as your friend rather than a burden that has to be learned in school.