I really enjoyed working in data science. Since my sophomore year, I already knew that I want to use technology as a way to solve real business problems. It gives me meaning to work and I hope it does for you as well.
Every day I would squeeze every bit of my time to read and learn. I would sign up for the local Data Hackathon and organize analytics related events to learn from industry leaders. I spoke in conferences and university events to mentor my juniors on how to succeed as a data analyst in large tech companies. I imagined myself as a fellow student to influence as many of my juniors as possible to learn and give back to communities.
If you say that this end goal might sound too noble, you are right!
In fact, as a Christian, I learned that time is precious, the mother earth is a terminal where we only reside temporarily. Nothing in the world is lasting including time. So we need to create and deliver as much value as possible to prepare for the everlasting life with God ahead. For me, my religion and data career has given me meanings to excel, to learn and to contribute.
After my admittance at Google as a Data Analyst to develop better ML Models to fight abuse, I have received many requests to share my life journey and tips for my juniors to ponder on. Therefore, I really hoped that this blog could fulfill that demand to give you the starting points to be successful as a data professional.
My biggest tips to aspiring Data Professionals
As we have known, data science and analytics have become a fast-moving industry with the highest growth over the past few years. Just within a few years, many universities started providing specializations in Data Science with thousands of sign-ups from all around the world.
Even in Singapore, there were no such programs 5 years ago, but now, the entrance of this degree has become as hard as getting into law and business school.
However, despite the rising trend, there are so many uncertainties about where the excitement is going. The job market for a data scientist is becoming more and more saturated and delusional.
Many startups are starting to realize that they are moving too fast in data science and start laying off their data scientists.
Therefore, to secure your future, you will need to mature quickly and differentiate yourself from your peers. Just like a war, You would need to start preparing your armory. The best way is to contribute more: learn, write, speak, specialize, and chill more.
Learn: The fuel of Data Science
Keep experimenting with your learning styles (kinesthetic, auditory, visual).
When I was learning, my friends always gave me lists of curated Machine Learning materials. But after reading and listening to lots of videos, I realized that I was a kinesthetic type (learned by doing) and I retained very few from listening. Knowing this information, I created my own projects which I documented on Github. Surprisingly, these projects had become the key for me to get into Visa and Google.
Similarly, do not blindly follow the conventional learning materials that your friends suggest. Do your due diligence and always have a trial and error mindset. Soon, you will find your best learning style to boost your skills.
For me, I usually use many different kinds of sources from Youtube and research papers. Personally I enjoyed Sentdex and Computerphile. Highly recommend for you to watch these videos and even better, reproduce them.
Furthermore, I am also taking a part-time online master’s degree at Georgia Tech which exposed me to deeper technical rigor of machine learning and statistics.
Always experiment, trial and error for you to learn quickly about this exciting industry.
Write: The legacy of Data Science
Write articles, share your codes to github, even better create a Youtube channel.
During my university time, I started writing online tutorials for my juniors to tackle their university projects. Once I formed those tutorials, I would set up some small sessions to nurture a study group and shared some machine learning related models. By sharing, I had fun and learned to articulate my thoughts.
Similarly, I also believe you will learn more as you write more. Every time you write some projects, you will be able to reflect on a certain model/test/code review. It will allow you to close your gap of knowledge and figure out how to upskill and find better solutions.
So far, I find Medium as one of the best channels to write on. It gives a sleek and standardized look for everyone to write, which free you the hassle to deal with the visual layout. Everything in Medium is already optimized for you to read and write.
Even better, you can also sign up for the metered paywall. This will give the opportunity for curators to distribute your articles and improve your readership. So far, I have released 30 articles with a few producing $300 USD per article.
Honestly, I think the best benefit of writing is that you get the chance to articulate your learning. It does not matter whether you blog online or even make a youtube channel. The goal is to maximize your time to learn and promote yourself.
Speak: The speaker of Data Science
Teach your fellow peers or any conferences out there!
When you speak, you are distributing your knowledge for others to use. You are promoting both yourself and your company. In the long run, you would be the more valuable data scientist because you have inspired your juniors to do the same. You will differentiate yourself from your peers.
Furthermore, speaking will give you further meaning to learn. The more you learn the more you speak. Similarly the more you speak, the more you learn.
Initially, I would send emails to university, data conferences, and youth groups to see if I could share some of my writings in data science. I have been fortunate that a few students groups at Singapore Management University (SMU) and the National University of Singapore (NUS) have been receptive to my requests.
When I speak about my knowledge, I not only inspire my juniors but also learn from them to communicate my thoughts well.
Specialize: The expertise of Data Science
Try to dig deep into a certain data science technique to complement your strengths (Business, Social Science, Sales, etc)
Have your own mindset and stick with it. Most of the common misconceptions are that business students would lose to IT students due to the needs of technical expertise.
This is not accurate.
A lot of superstar analysts I know come from various backgrounds such as Social Science, Business, and Economics. They use analytics to complement their expertise.
Therefore, stay calm and leverage your strengths rather than indulging on the latest Kaggle’ ish analytics trends such as Random Forest, XGBoost, etc
For example, if you come from a finance background, you can develop your own stocks analysis project. If you come from operations and inventory management, you can focus on JIT (Just In Time) analytics to minimize bottlenecks and maximize efficiency. The sky’s the limit when you use analytics to make data-driven analysis on your domain.
For me, I come from a software development background. But I used business analytics to communicate my skills by developing a simple product.
One day, I asked my friends who are finance students how they analysed stocks.
Their answers surprised me as they used the most time to copy and paste each data from Google Finance into an Excel sheet and analysed them. As a response, I created a simple program to web scrape and generate intrinsic values using Value Investing methodology. This has become the flagship product that I share with my fellow students at SMU.
Chill: The fun of Data
Avoid burnout and have fun while hacking
A personal relationship is important in life. Therefore keep hacking with your friends. Use your Saturdays to learn and Sundays to chill.
Furthermore, join learning minded companies. Visa and Google are a few of them. The best thing about working in tech companies is that you get paid to learn critical skills that would be in demand in the years ahead.
For me, I am very happy to avoid burning out by chilling with my friends at church. Whenever I have free time, I would work out.
I would train for a marathon, triathlon, and even cycling trip overseas (recently 515 km all over 3 days at Java Island Indonesia). It is very busy, but it is very fulfilling and I would re-energize once the new Monday starts. Soli Deo Gloria.
Finally…
I really hope this has been a great read and a source of inspiration for you to develop and innovate.
Please comment out below for suggestions and feedback. Just like you, I am still learning how to become a better Data Scientist and Engineer. Please help me improve so that I could help you better with my subsequent article releases.
Thank you and Happy coding 🙂
