Student Spotlight: Ho Fai Wong of NYC Data Science Academy

This article is contributed by CourseReport, a third party website specialized in covering bootcamp stories.

Ho Fai has an impressive career in IT Infrastructure for consulting powerhouse PWC. When he realized that he clearly loved gleaning insights from data to solve his clients’ problems, Ho Fai decided to invest more heavily in his Data Science skill set. His company agreed to let him take a sabbatical and enroll in NYC Data Science Academy, with the aim to make his skills even more valuable to the business. Here, Ho Fai answers all of our questions about his experience at NYC Data Science Academy!


What were you up to before you went to NYC Data Science?

I've been an IT infrastructure consultant since 2007, originally for BearingPoint, whose North American Commercial Services practice was acquired by PWC in 2009, and I became a Manager in 2013. I consult for different industries - primarily financial services but also airlines, hotels, pharmaceuticals, automotives - but always around IT and usually IT infrastructure.

What’s an example of an IT infrastructure project you’ve worked on in the past?

In the world of consulting, every project is different, but to give you an idea - in one project, I worked with a company to assess their current state of technology in terms of compute, storage, network, etc, and helped define their vision for the next 5-10 years. That’s a high-level strategic project, but I’ve also worked on more tactical projects to help clients actually migrate data centers or separate from their parent companies.

Do you have a CS degree? What type of education do you need in order to get that job?

I studied in France at the Ecole Nationale Supérieure des Télécommunications. The French “Grande Ecole” system is a bit different from what we're accustomed to in the US, but I essentially obtained a Master’s degree with an emphasis on Computer Science and Networking with dashes of Economics and Macroeconomics.

Do you have a background in programming at all?

Only basic Java and C++ from my academic studies in my Master’s degree. Over the course of my consulting years, I didn't really do much coding per se, because I was more of a strategist in technology consulting, not a developer. The only coding I did on the job was in VBA in Excel, and some SQL.

What inspired you to start looking at data science bootcamps?

Throughout my years of consulting in IT infrastructure, I’ve always solved clients' issues using bits and pieces of data science, gleaning insights from data to solve the client's problems.

After taking stock of everything I've done so far - I realized that's the piece I enjoy the most. After talking with friends in Silicon Valley who went into data science, it confirmed that the combination of programming, math, data visualization and communication to end users is my passion and my forte.

How did you find out about NYC Data Science Academy in particular? Did you research other data science bootcamps?

Like any good consultant, I did my due diligence! I made a spreadsheet and compared curricula, price, time/length and so on. I also talked to some of my data science acquaintances to get their perspectives on these data science bootcamps. The curriculum and timing at NYC Data Science Academy made it the most appropriate choice.

Your story is unique because you didn’t quit your job to do a data science bootcamp. Instead, you approached your company about taking a sabbatical- what was their reaction when you pitched it to them?

In a nutshell, overwhelmingly positive. I've been working for PWC for quite a while, and I have developed great relationships. I am tremendously appreciative of all the mentors in the company who support my career decisions and development. I'm planning on returning to PWC after graduating from the NYC Data Science Academy, where I have the flexibility to reorient myself within the company into different groups or even help develop a practice using these data science skills that I am acquiring.

PWC definitely sees the value of these data science skill sets. It was a no-brainer for me to ask my management, and it was a quick decision for them to agree.

Does your company offer education benefits? Did they actually pay for the bootcamp tuition?

PWC is huge on personal development. In consulting, the people are the product, so the skill sets and experience of the consultants is what our clients are paying for. PWC is huge on providing learning and development- both internal and external. And beyond that, there's actually a budget devoted for each employee to invest in learning that may only have a tangential relationship with your current position.

Tell us about the application process for NYC Data Science Academy. Did you have to learn any Python or R in order to do the coding challenge?

There were two coding exercises, which I found relatively simple, but that simplicity depends on your background. Having had some level of programming education or experience definitely helps, but it didn't have to be in Python or R. My Java and C++ skills were rusty so I actually answered those coding questions using VBA, which isn't necessarily a popular development language, but they accepted it.

NYC Data Science Academy didn’t mind the choice of language as much as seeing that you can think in terms of programming logic. The point of the bootcamp is to teach you skills that you don't know in a really short and aggressive timeframe.

What is your cohort like? Did everyone come from a similar background as you?

Oh, it’s definitely an extremely diverse group. I am the only management technology consultant. Folks come from academia, research, some just graduated, math PhDs, architecture, law, etc. Data Science as a field probably skews a bit male, but we do have quite a few women in my class.

What's been the biggest challenge for you in the first six weeks?

Personally, my biggest challenge is in statistics. Even though I was rusty in coding, I can pick up computer science concepts and languages pretty quickly. My strong suit is in data visualization and storytelling; the actual analytical process of sifting through data to reach findings and presenting them clearly and succinctly.

Statistics - especially theory - is the area I’m putting most of my emphasis and focus on. That's only my personal story, though. All the people here have such different backgrounds;some might be familiar with statistics but face challenges learning R or Python, and vice versa.

After graduating from a Master’s program, what do you think about this immersive 12-week education style? Is it working for you?

It is definitely working for me. I’m not in university anymore; I don’t have the freedom to spend years slowly learning, and figuring out my life plan. I need an aggressive timeframe and the fact that a bootcamp is able to condense so much into such a short timeframe, but still do a really good job of covering theory to practice, is honestly phenomenal.

If you're in a career-oriented mindset, bootcamps are the way to go. If you have the leeway, flexibility and the luxury to be a student for a couple of years, then university may be a good option for you.

What’s the teaching style? Does it work with your learning style?

It's an awesome mix of lectures and projects. The structure of the bootcamp is one of the things I like most about being here. We always have a couple of hours of lectures in the morning. In the early afternoon we usually have homework review followed by either guest lecturers or project presentations and the rest of the time we work on homework, projects, Kaggle competitions, third party vendor and recruiter visits, and resume reviews. All of that mixes together so that you don't get bored or feel overwhelmed by one specific topic. It keeps things fresh. On the flipside, you need to learn how to juggle.

After six weeks at NYC Data Science, tell us a bit about the projects that you’ve done.

All of our projects thus far have been based on our own ideas. That’s fun and paradoxically stressful at the same time, because the world is your oyster. The choice and selection of the project is up to you, but so are all the downstream impacts, challenges, delays, etc. That approach is great, because you're more likely to be invested in the actual topic of your project if you choose it yourself.

At the six week mark, we are assigned a project that’s based on a Kaggle competition. The teachers want everyone to use the same dataset with the same objective to assess where everyone is halfway through the program.

What's your favorite project so far? Can you tell us about it?

My favorite project was a Shiny web-based application because I like the visualization aspect of it. Shiny is a web-based application development framework. In our case, we tied it to R, and essentially from R we could create visualizations that are easily transposed into a web-based application.

I chose to analyze World University rankings. I studied in France in this system that is quite prestigious but that most have not heard of outside of France. I wondered what determines if a school is “good” and prestigious or not. Kaggle actually had past datasets from world university rankings so I visualized the rankings of all the universities in the world by these three organizations. A user can play around and visualize by country, by university, and more importantly compare how different ranking organizations tend to rank drastically differently.

NYC Data Science Academy, like most bootcamps, is focused on job placement after you graduate. Since you already have a job, are you planning to skip the job prep section of the course?

I’ll probably still participate, just to polish my skills. For example, the code review sessions (i.e. which are basically interview coding exercise prep simulations) are useful to sharpen coding skills under time constraints. I have found it really interesting to solve problems under a time restriction - that’s great preparation for a career as a data scientist.

What are your plans after you return to PWC? Will you move into a pure data science role, or use your new programming skills and machine learning and data visualization in your current role?

Figuring that out is on my to-do list! So far I have had conversations, done some research and discussed with colleagues at PWC. There are several teams where I could use these skill sets but figuring out precisely which one is still up in the air!

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