Data Science Career Spotlight: Brian Leung

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Today, we’re beyond thrilled to chat with Brian Leung. Brian is currently the Engineering Fellow at Tune into our chat as we learn about Brian’s career path and his story:

Tell us a bit about your background, and how did you pivot into becoming a data scientist?

I did my undergraduate double majoring in Computer Engineering and Math, then came across Biomedical Engineering as a possibility of interest, which later on prompted me to pursue a master and a PhD in the respective field. After that, I wasn’t planning on staying in academia, I ended up in the field of Pediatric Rehabilitation, where I helped children with disabilities to use computers through electrical engineering practices. The techniques and skills I acquired are all transferable to an extent where it’s not unlike what a data scientist does. They helped shorten the gap, so it’s not really a total pivot for me.

Coming from a biomedical engineering background, what past experience helped you the most?

As I mentioned earlier, I started out in the field of Pediatric Rehabilitation, essentially what I practiced was building devices, signal processing, pattern recognition, multidisciplinary development with people from different backgrounds. Combining together, they all helped bridge my way into becoming a data scientist.

What does your day to day look like?

My day to day is in constant flux. I take responsibility for every aspect of data that flows in and out of the team and synthesize insights to help support the decision making process. Sometimes I make sure the data pipeline is operated properly, other times I fulfill data requested from other teams. Aside from that, I also helped develop the dashboard as a software engineer. It’s very important to be flexible and know how to prioritize.

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What’s the most challenging part of your work?

Business acumen and time management. It’s very essential to know how to balance between the level of detail in terms of the analysis you want to do, communicate to the right audience, budget time investment between learning new software tools and actually creating and delivering insights and analysis.

What’s one thing you wish you knew before entering the field?

The importance of seeking mentorship from industry experts. Following the mentorship of someone who is a bit more established as you starting out can help you understand the industry, working environment. Especially translating from academia to industry, adjusting to the timeline and the environment are crucial. For example, learning how to accommodate other people’s timeline and communicating clearly and at the right level of detail.

What’s the most essential skills or tools you can’t live without?

It depends on which role I am fulfilling. For example, as I’m doing data engineering, it’s SQL, for software development, git and Python are the major ones. However, technologies are constantly updating, at the end of the day, it always circles back to the consumer of the data. It’s important to facilitate how others access and use the data instead of enforcing a particular technology that others are not fluent in. In terms of the data consumers, you want to make sure they are able to do the work with the tool they are proficient with and have the access to the data where they can trust to develop insights on. The ultimate goal, data democratization, would eventually allow people to access the right level of data at their convenience at the right level of granularity with things they want.

In terms of the interview, what quality or skill you think would help an interviewee stand out the most?

I would say their interest level in data, the industry and knowing why they want to enter this field. Also, how do you envision yourself growing in terms of being a better data scientist? The reason being as glamorous as certain aspects of being a data scientist, we tend to focus too much on machine learning and deep learning. However, looking back, most of my time is trying to ensure the data integrity so that we can deliver insights confidently. Understanding that it’s not so much about technology, more about how to communicate at the right level to the target audience.

What advice do you want people to take away with?

In terms of the career, picking up the non-technical aspect and developing a business acumen. For the industry, asking yourself what kind of company you want to work for, start-up or ones that are already established. Lastly, during the interview, asking for their expectation so that you could set yourself up at a place where you will be able to succeed.

About the Author: 

LinnaLinna graduated from University of Waterloo with a degree in Bachelor of Science. She is very enthusiastic about data and integrating tech to turn it into meaningful insights to propagate better strategies. She is a lifelong learner and always excited about new technologies. Connect with Linna here