Christopher Woloshyn is an example of how to make the most of your time ant Binghamton University. Read about Christopher’s time as a Residental Assistant (RA) and how he double majored in Mathematics and Cinema!
Major(s) at Binghamton University: MS in Systems Science; BA in Mathematics, Cinema
Career Cluster: Engineering & IT
What activities and clubs/organizations did you participate in during your time at Binghamton University? This could include on-campus employment, research, volunteering, study abroad, student organizations, etc.
As an undergraduate student at Binghamton University, I was heavily involved with the Hinman living community. My first two years, I lived in Hughes Hall on the Public Service Learning Community (PSLC): a volunteer oriented living community centered around community engagement and involvement. My second two years, I lived in Cleveland Hall as a Resident Assistant, where my involvement centered around creating unique, inspirational, and educational events for students living on campus, inspiring them to be involved in the community and understand what makes Hinman such an amazing community. I was also involved with the Hinman College Council.
Outside of Hinman, I volunteered at Vestal Hills Elementary School my first year, and consistently volunteered with Bridging the Digital Divide with their Computer Refurbishment Program. I also worked as a ResLife photographer and videographer where I did event photography for Residential life as well as direct, shoot, and edit promotional videos for ResLife.
I was also a member of the following honor societies: National Residence Hall Honorary (NRHH), Pi Mu Epsilon Math Honor Society, Phi Beta Kappa honor society.
How did your experiences outside the classroom influence your career development?
My experiences outside of the classroom, particularly my involvement in Hinman, taught me a lot of interpersonal skills. Being an RA was an extremely rewarding and important experience for me. In many ways it taught me a lot about working on a larger team, meeting regular recurring deadlines, and working with a diverse and energetic group of people. The setting was also more akin to a “corporate” experience than my classes were as well which made the experience feel more one-to-one. I’d like to thank Amber Wade and Diana Shcherbenko in particular for being such amazing and supportive cornerstones of that experience.
Why did you select your major at Binghamton University? What experiences or factors influenced your decision?
For my undergrad majors, the decision to pursue Mathematics came from me trying to be prepared. I was a student of Harpur College, but while I was undecided, I wanted to take classes that were aligned with general engineering in case I ever wanted to transfer into Watson College. Eventually, I decided to double major in Mathematics and Cinema because Mathematics captures a lot of similarities to engineering, and possessed a lot of career potential, while giving me the flexibility to also study Cinema as a passion.
For my graduate major, the decision to study Systems Science came because of me being one of the first students to enroll in the Master of Science in Data Analytics (MSDA), and the program being deferred due to low enrollment. Dr. Hiroki Sayama came to the rescue by showing me how amazing the MS in Systems Science program is. As a combination of Applied Mathematics and Computer Science, it was the perfect program to enroll in for pursuing Data Science as a career.
What advice would you give to a student who is exploring different major options?
If you are unsure about what to major in, put in the hard work early to leave as many options open as possible. I came into Binghamton as an Undergraduate with a lot of AP credits and Gen Ed requirements covered and continued to take a diverse set of classes to leave my options open. This gave me the opportunity to elect to transfer (intra-university) into Watson or SOM and gave me the freedom to comfortably choose a Major after being exposed to a wide variety of classes, AND I was able to do so without losing any time.
How did your coursework at Binghamton prepare you for your current role?
Many of my Mathematics courses, while they haven’t been directly relevant to my work, taught me an entirely different framework of thinking oriented around definitions and logic. As it turns out, this is an extremely useful skill to bring to working environments.
Learning how to approach math problems emphasizes the importance of this mode of problem solving, and I think it has been a valuable addition to any team I’ve been a part of.
What class at Binghamton University was the most influential to you and why?
For me the most influential class I took at Binghamton was either MATH 225/226 (calc 2) with Professor Bill Kazmierczak or CS 110 with Professor Steven Moore.
Taking calc 2 with such a fantastic professor cemented my interest in math and was the catalyst for my decision to major in Math the next fall.
Taking CS 110 my junior year showed me how mathematics and the associated thinking patterns can be directly applied in the real world. It added a tangibility factor to what I was learning that felt like it existed outside of academia or learning for the sake of knowledge. In other words, if learning math was a strong wind, learning the basics of Computer Science was a proper bearing.
What would you say is the most important skill in your field and how do you use it in your current position?
In general, I think having very strong fundamentals for the primary skill in your career or desire job is the most important skill to have when starting a career. I would assume this applies to any career field, but for me as a data scientist, I think there are two foundational pillars that have bolstered my success in my current position:
1) Strong understanding of mathematics/statistics concepts
2) Foundational programming/ computer science skills
Being early in my career, I have found that having strong fundamentals gives me the flexibility to perform well on a broad range of tasks and job requirements. At EY, each project can vary by a large margin of required skills; having these strong fundamentals makes it easy to learn new, potentially more niche skills, and rapidly adapt to the required skillset for the project. For example, having very strong mathematics fundamentals and experience in complex systems simulations and modeling allowed me to onboard to a financial modeling project very quickly, despite having no prior experience in financial modeling directly. Many technical skillsets are transdisciplinary because mathematics is application agnostic.
How can Binghamton University students develop this skill while in college?
Data Science is one of the fastest growing fields in tech, and therefore it is also one of the most competitive fields in tech. There are myriad boot camps, certification programs, and self-learning opportunities (e.g., YouTube, MIT OpenCourseWare, etc.) available offering opportunities for people to “pivot into a career of data science” in 6 months or less. While any of these approaches can lead to success in their own right, I think the scope of skills that are learned is far narrower. One of the advantages of Binghamton, or any conventional university, is that the course structure offers a fundamentals first approach, and this in turn can give you a competitive advantage in the pursuit of your job or career.
Another amazing skill unique to the college experience is learning “how to learn.” We are subjected to dozens of professors, all with different teaching styles, coursework, and evaluation methods. I think this is one of the most valuable aspects of a liberal arts degree, especially since most people with college degrees in general tend not to work in a field directly relating to their major [https://libertystreeteconomics.newyorkfed.org/2013/05/do-big-cities-help-college-graduates-find-better-jobs/]. In my opinion, knowing how to learn new skills quickly and effectively is a massive component of your degree that will help you in the job world.
Engineering is a bit different, since you are much more likely to work a job directly related to the engineering skills you learned, but I think this concept still applies. It’s both a combination of strong fundamentals with the ability to learn quickly that gives an advantage over, e.g., an equally qualified candidate without a four-year degree.
If you were hiring a new graduate for your company, what skills and experiences would help this candidate stand out?
To me, internship or project experience stands out the most; this is the thing on your resume that takes what you theoretically know and demonstrates that you can apply it towards something relevant to the person/organization looking to hire you.
What tools and resources were most helpful to you during your job search?
The two most useful tools/resources are LinkedIn and a person you already know that has the kind of job you’re looking for. LinkedIn is probably the single most useful tool for the job search. LinkedIn is a hub for recruiters and bots to scrape through thousands of profiles and match them to the roles they are trying to fill. Keeping an up-to-date LinkedIn profile will keep your name cycling through these systems and increase the likelihood a recruiter will reach out to you with an opportunity. This is important because applying to job via recruiters or with referrals from people you already know will close to guarantee an interview, whereas cold applying to jobs usually has a less than 1% “hit rate” for landing an interview, and I can prove this with data!
During my job search leading up to the job that I currently have, I kept track of every application I submitted:
– From 58 total applications, 48 were cold applications, 3 were applications from a referral, and 7 were applications through a recruiter that reached out on LinkedIn.
– From the 48 cold applications, 46 had no response and 2 were rejected (0% interview rate). From the 3 referrals, 1 had no response, 1 was rejected, and 1 lead to an interview (33% interview rate). From the 7 recruiter applications, 7 lead to an interview (100% interview rate).
– From 8 interviews, 2 had no response, 1 was rejected, and 5 lead to a second interview (62.5% interview pass rate).
– From 5 second interviews, 1 had no response, 2 were rejected, and I received 2 offers! One was a remote position from a small company I hadn’t heard of, from a recruiter application, and the other was EY, my current employer, which was from a referral.
What is your advice for writing a strong resume/cover letter for a position in your field?
A strong Resume is two things: simple and “parse-able”. My resume still is based on the style and format used by the Fleishman Career Center because it meets these two criteria. It is a simple format that maximizes space and clearly organizes each component of my experience, and it is “parse-able” meaning a bot can easily separate that information with minimal errors. This is important because recruiters use software to parse thousands of resumes, extract important keywords, and match those keywords to keywords in the job description. A strong resume will maximize these keywords with respect to the job you are applying for.
What is your advice for interviewing for positions within your field? How can recent graduates stand out?
Knowing how to communicate and emphasize the relevant aspects of your project or internship experience (e.g., technologies used, accomplishments, skills) helps the interviewer understand “oh, this candidate has done work very similar to this.”
Specific to data science, a solid understanding of computer science fundamentals stands out to me a lot. There are a lot of graduate students and posts on LinkedIn of people sharing their personal projects. Very cool analyses and visualizations usually, but the main limitation to these projects come from when I look at the GitHub repository and only see folders of Jupyter Notebooks. To me, this type of project doesn’t demonstrate your ability to extrapolate your knowledge to a “real world” use case and end up looking more like a recreation the notebooks made when following along a Udemy course.
This is just one example, but I also have a personal bias against Jupyter Notebooks because of past horror stories having to refactor models built in massive, undocumented, buggy notebooks; to me, the fundamental computer science skills around software/module design and documentation REALLY stands out as a result.
What is one thing you would suggest students do before graduation to be more prepared for the job search?
Be prepared! If you are trying to get a FAAMG job (Facebook, Apple, Amazon, Microsoft, Google), study, study, study! LeetCode and Cracking the Coding Interview: THERE ARE NO SHORTCUTS FOR FORTUNE 10 COMPANIES. If you aren’t trying to get a FAAMG job, I think all the same things apply, but just to a less extreme extent. If you learn how to play the game, you’ll have an advantage over other players.
What’s the best piece of career advice you have received?
It’s never too late to change your path! I decided to pursue data science only a few months before graduating! Thankfully, the pivot was easy because of my background in math and little bit of Python experience, but so much time is spent working that it should at least be something we’re interested in, or else 2000 hours (or about 1/3 of our awake time) will just be miserable…
