Written by Hui Xiang Chua May 5, 2020
Based in Singapore, Hui has built deep expertise in statistics and analytics, which led her to become a professional in Data Science. As a mentor, she wants to build the confidence of people who are in the same shoes as she was, and help them break into the Data Science field
Hey Hui! Tell us a little bite about yourself!
I joined in March 2019 and was glad to chance upon MentorCruise while searching for a platform where I could guide people on their data science journey. I personally found that I had benefited a lot from my mentors during my academic days and I hoped to do the same for my mentees on here.
My background is in statistics and that really built the foundation for my path towards data science. I subsequently did a Masters in Business Analytics. Data science is nothing new but a convergence of statistics and computer science, to be honest, so my background in those areas aligned very well.
I’m glad that more people are interested in this field. There are so many problems that can be solved using data and tech! I think it’s important to understand the business problem and what the data represents whenever we handle any data science project.
Did you ever have a strong mentor in your life? How did they help?
Yes! In fact, I was lucky to have a couple of strong mentors that really shaped my growth and I am thankful to have had their guidance.
My undergraduate thesis supervisor was the one who got me interested in research and gave me confidence in coding/ algorithms. I was really struggling in programming and had doubts whether I am suited for technical work.
Under his guidance, I really found joy and satisfaction, seeing how math and statistics could give insights into real-world problems. I’m glad that I didn’t shy away from this field in the end.
How do you usually set up mentorships? How and how much did you communicate? How did you track progress and keep things going?
Typically I try to understand the challenges my mentees are facing and the goals they have set out for themselves to achieve, so that I can help them get to where they want as quickly as possible.
We usually communicate through video chat and email on a weekly basis but of course, there are instances where some mentees have ad-hoc assignments and they just needed one-off help which I am also happy to do so.
Tell us about one of your best past mentorship experiences!
Each mentoring experience is memorable to me because every mentee is always so passionate about what they are doing. It makes mentoring a lot easier. I’m also thankful for mentees being receptive as well.
What are you getting out of being a mentor?
It’s always interesting to hear the kind of data organisations are collecting as part of their service and how people are making use of the data to bring more value to the organisation/ consumers themselves.
There are some occasions where I might not have practical experience (be it at work or outside of work) and this also prompted me to learn more in those aspects.
What’s your best advice for new mentors out there?
You probably heard this a lot, and it’s true: Mentoring is a two-way street, both parties learn at the same time. There’s always talk about the imposter syndrome and I think we have to come to embrace the fact that all experiences are valuable.
What is the most crucial skill to learn for people entering data science?
This might not exactly be a skill, but I hope that whenever we perform any analysis or develop any product, we don’t forget the humans behind the numbers/ data.
And to wrap things up, where can we find out more about you and your work?
I run a data science blog called Data Double Confirm and it’s been selected as Top 100 Data Science resources on MastersinDataScience.com in 2018/ 2019 and Top Active Blogs on #AI, #Analytics, #BigData, #DataScience, #MachineLearning by KDnuggets in 2019.
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