In the age of automation, there was one job that was supposed to be beyond the reach of robots: artist. That, however, may be about to change.
With an undergraduate degree in Pharmacology and a Masters in Finance, Hannah Cheng is no stranger to post-secondary education. Recognizing the need to develop digital skills to align with job market demand, Hannah decided to apply to BrainStation’s Data Science Diploma Program.
We asked Hannah about her experience in the program and how it helped her land a Junior Data Scientist role at EllisDon.
Can you tell us a bit about your education and career background before BrainStation?
Prior to joining BrainStation, I was a graduate from the Master of Finance program at McGill, and before that I completed a BSc in Pharmacology and Therapeutics, also at McGill.
I had some internship experience working at a medical research lab in a hospital during my undergraduate degree, and when I made the switch into finance, I also worked as an Equity Analyst for the healthcare sector.
What was your motivation to take the Data Science Diploma Program? What factors influenced your decision?
The greatest factor that led me to take BrainStation’s Data Science Diploma Program is the fast-paced evolution of the industry in terms of tech, the competitiveness of the job market, as well as my own ambition. Upon graduation from graduate school, I’ve come to realize that many jobs require a certain level of coding skills, regardless of the specific language. Furthermore, as someone who chose a different career path –from science to finance– my lack of work experience in [finance] made it more difficult to land a job.
That being said, from experience I knew there was an abundance of data to be leveraged and utilized in both the healthcare and finance industries; I had the technical knowledge back then, but lacked the skill-sets to execute those analyses. I thought it was only natural to make the transition and pick up some coding and technical analysis skills that could boost my resume and competitiveness in the market.
So to sum it up, taking part in the diploma program was an incentive to bolster my marketable skill sets, but also because it complements my education background.
Tell us a bit about your learning experience at BrainStation, what are some of the highlights?
I really appreciated the instructors’ patience and expertise in helping the students getting through a steep learning curve. Especially our associate instructor Stephen, he created a really a great learning experience and spent extra hours to help us with our capstone projects.
What were some of the most valuable skills you gained during the Data Science program? Why were these skills important to your professional development?
It was very important to understand how to think critically, come up with viable solutions, and how to execute to arrive at the solution. The datasets we used to run models in class are cleaned for us, while in the industry, 80 percent of the time will be spent on cleaning. Therefore, when a messy dataset is thrown at you, it’s very important to know how to take a step back and brainstorm and think critically – what is the problem, what are some possible solutions, and how can I go about achieving the goal? I think at the end of the day, thinking critically has always been a very important skill set in a professional development environment, but now you’re equipped with the technical skills to execute that, which is a very valuable asset.
Apart from the hard skills, it was great to leverage the connection BrainStation has already established within the Toronto tech community. As someone who came from a different background, understanding how the tech world functioned, attending meetups and events, really helped to ease the initial transition process.
How did BrainStation prepare you for the job hunt? What kind of career support was provided?
BrainStation provided me with the essential programming skills and a strong foundation in basic data science theories and knowledge.
Furthermore, I was given clear directions on how to position myself strategically during the job hunt process. For example, I received a lot of help from the education team when it came to selecting a capstone project. It was really easy to get side-tracked when we had to pick a project that is interesting to us, because it might not be as interesting to industry partners.
I mention the capstone process because ultimately this project is the communication between you and industry partners on Demo Day. It is the one time you can showcase to them what the 12 weeks were all about, what you learned, and what you are capable of; the capstone project is really a gateway to job hunts.
In terms of career support, I really enjoyed the tech tours as well as power hours that were hosted by some of the industry experts. It was helpful to see the world of data science and how it’s applied in the industry, as it is quite different from the class setting.
You’re now working as a Jr. Data Scientist at EllisDon, what was the process of finding and applying to that role?
I had the chance to meet the VP of Data Engineering and Products on Demo Day, and was able to keep in touch with him. I did two rounds of interviews with the Manager, the Director of Insights and Analytics, as well as the VP himself. The interview process included the standard behavioural sets of questions, and subsequently I presented my capstone project to the team.
Do you use the skills you learned at BrainStation in your new role?
Since Ellis Don is still in very early stages of production in terms of data management, at the moment it’s more exploratory work in its data science. I did apply some of the skill sets I learned in BrainStation, specifically the basic models and the workflow of dissecting a problem down and data preparation.
I think it’s quite different in data science as opposed to web dev or UX; there is no one hard set of rules or answers for a certain set of problems. The solution could be flexible and could be achieved in more than one way. It is important to understand the logic behind each algorithm and why you use it, otherwise one wouldn’t know when to apply which algorithm to solve an industry problem. I think BrainStation did a great job in building that solid foundation, and it is important to understand that it is okay to not understand 100% of the materials. Those couple months post graduation will be a crucial time to hone those skills and apply them on personal projects to showcase to potential employers.
Overall, I think the core, technical materials from BrainStation have helped me the most in my new role.
Has BrainStation influenced the way you view digital skills and professional development? How so?
Thanks to BrainStation’s vast industry connections, I was able to attend several tech tours and step into the Toronto tech world for the first time. Prior to BrainStation I wasn’t in touch with the tech community at all, and being part of the program helped me see how important digital skills have become in career development, and how it will continue to evolve in the future in terms of disruptive technology.
I am really glad to have made the decision to find a way to marry the two disciplines of my technical background and digital skills together. Going forward, I am looking to pick up a couple more programming languages, build side projects, and zone in on fields where expertise from finance, healthcare, and data is required.