Data scientists: the superheroes of data

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Most of the data science practitioners here are not doing the hardcore data science. They are either cleaning data, handling business intelligence or data analysis. This could be due to the market needs now, the readiness of companies to embrace data science or unfortunately, the lack of hard skills.
— Joanna Yeoh, Director, ConnectOne

Look at a job description for a software engineer these days and you’re likely to stumble across the phrases, “big data”, “data scientist” or “machine learning.” Data is truly the celebrity of our times. As we go online more and more, businesses are seeing unprecedented volumes of data (forget the terabyte, we are talking petabytes here!) enter their systems. Businesses not only have to tame this voluminous data, but they also need to interpret the streams of raw data flowing into their system constantly. With this deluge of data pouring in, businesses are desperately looking for help from the superheroes of data: the data scientists.

For international companies who have clients in Singapore and the region, there is a compelling need to source for local data science talent. Yet, this pool of talent proves elusive for smaller companies who need the heavyweights but may not have the resources to import their talent with them. Weighing this issue down is the mismatch between responsibilities and skills; data scientists often get mixed up with other data experts such as data analysts and big data professionals.


Let’s be clear, what is data science?

Data science usually refers to either machine learning or deep learning. With deep learning, you need a huge amount of data in order to make sense of it. In the real world, there are not that many areas for deep learning because of data limitations. Take us for instance, you can’t force more transactions to happen in the Singapore housing market so we can have more data. While deep learning is often the focus of the media, machine learning definitely has more real-world applications.
— Mike Cho, Founder, UrbanZoom
Mike Cho, Founder,  UrbanZoom

Mike Cho, Founder, UrbanZoom

It wasn’t too long ago that the work of data scientists was the same as computer scientists. As the volume of data kept growing, the discipline morphed from computer science to business analytics and data analytics. With the dawn of Big Data, it shifted again to what we now, think of as data science. How it shall evolve depends on the state of future data.


Surprisingly, the first use of “data science” can be traced all the way back to 1996 when it was used as a conference headline. But it really was the 2012 Harvard Business Review (HBR) article that made the term mainstream. The HBR article profiled data scientist pioneer Jonathan Goldman and his work on predicting recommended connections for Linkedin Users, bringing the term, “data scientist” as we know (and love!) today into popular usage.


Can a data scientist by any other name, still be a data scientist?

After the 2012 HBR article, data science as an industry genre started trending and there was a sudden surge in “data science” courses. But as it turns out, many were business analytics courses that rebranded themselves to cash into the data science trend. This led to confusion in the market around what these different data experts did. In addition to existing analysts, there was a new breed of data experts but they seemed to be doing the exact same work as data and business analysts!


Thankfully, six years on, more clarity has emerged. It’s now clear that all three disciplines deal with statistical models and use data to drive decision-making. It’s this overlap that has created a fluidity between these roles that can be confusing. Let’s take a look at the three most commonly confused data expert roles:

  • Business analytics typically deals with information in the past to gain insight into business planning. Business intelligence, a subset of business analytics, is interested in historical business data. They both use descriptive statistics and reporting or visualizing data of past events. They work with data science if they need predictive modeling to gain insight into the data.

  • Data analytics occupies more of a grey area and can overlap into the work of a data scientist in early startups. Typically, it deals with structured and “cleaned up” data to draw conclusions and provide insights but more experienced analysts could map raw data and convert it for consumption. Data analysts are often also responsible for data visualizations for the businesses, creating reports and dashboards.

  • Data scientists can dabble in data analysis in the course of their work but their primary focus is to engage with the data from multiple data streams to detect patterns that can help him create predictive models. They also bring structure to formless data so statistical analysis is made easier and more accurate. They can choose to specialize in data cleaning, data shaping or machine learning.


Singapore: A unique challenge

First, the facts. Singapore is serious about data. According to EDB, data analytics annually contributes about S$1 billion to the Singapore economy with regional data analytics services projected to reach S$27 billion. Singapore is also playing host to Facebook’s data center, poised to open in 2022 as well as Alibaba’s first joint research institute outside China.

Second, the talent. An overview of Linkedin shows that there are about 2000 professionals in Singapore who identify themselves to be in data science. The experience of these professionals seem to be evenly distributed; individuals who identify as having more than 10 years, 6 to 10 years as well as 3 to 5 years of data science experience all hover at a similar proportion. Unsurprisingly, a large proportion of these candidates are employed by Grab.

Despite these promising numbers and the support from the government, the challenge to find high-quality talent in abundance persists.


What are the superpowers of a data scientist?

I look for 3 key sets of attributes:
(i) a fundamental understanding of math and statistics, (ii) the ability to code beyond the lab to code in productions, and (iii) the ability to communicate within a specific domain. The last one is probably the most important. We’re not looking for a generalist. We need someone who can ask the right questions and apply data science appropriately to solve a problem within a specific domain
— Ken So, Founder, Flowcast
Ken So, Founder, Flowcast

Ken So, Founder, Flowcast

Who better to shed some light on what the market is looking for than the market itself? We mined insights from two startup founders: Ken So, founder of Flowcast, a Silicon Valley fintech startup with clients in Singapore, and Mike Cho, founder of Urban Zoom, Singapore’s first AI property valuation tool.

Both Ken and Mike are in agreement on what they look for in a data scientist:

A well-rounded technical person who has the soft skills and capability to apply theory to real-world issues. If it sounds like everything, well, that’s what sets apart exceptional data scientists from the average!


A technically strong data scientist makes analysis easier but more importantly, creates an ongoing relationship with data so that it can be meaningfully used to support business decisions. But that’s not enough! A technically strong data scientist who has the relevant soft skills will be able to hold his own in a business setting, using the relevant communication skills to tell a story with the data, shaping stakeholder perception and guiding business decisions.

Mike says, “Aside from the usual expectations of being self-reliant and a team player, a data scientist should ideally have the full suite of skills, with exposure in data gathering, data cleaning, data shaping, and machine learning. Frankly, for our work, algorithms are about 10% of the work. 90% is about cleaning up real-world data because real-world data is dirty. Only a full suite data scientist would be able to deal with it adequately.”


Challenge of grooming talent in the region

Not many data science candidates come in with the commercial and practical experience we tend to see in Silicon Valley.
— A pressing difference in data scientists in SV and Asia

The challenge for grooming talent is exposure. Ken points out, “In the region, excluding China, there is an expectation that Singapore will have the concentration of talent. However, there is a noticeably heavy emphasis on academic thinking and theory that we see in candidates from around here. Not many data science candidates come in with the commercial and practical experience we tend to see in Silicon Valley.” He adds, “US companies have been investing in Big Data and its infrastructure for years. Now they are in the phase of deploying data science solutions. By contrast, Asian companies are still behind in that investment and deployment cycle.”

 
Top talent is always going to be where the big data is going to be.
— Mike emphasised the challenge of finding top talents in a small market

Mike believes one of the key issues is the inherent market size. “I have been to data science meetups in Singapore and they are undoubtedly well qualified, but the discussions in Silicon Valley are definitely more sophisticated and have more depth because of the problems they are trying to solve.” He says, “If your market is only going to be Singapore, there just won’t be enough data. Top talent is always going to be where the big data is going to be. In the size of a market like Singapore, the data is unlikely to present the interesting problems required for deep learning.”

While the facts seem sobering now, the government’s interest and investment into data will definitely boost the industry and the quality of talent available. In early 2018, NUS partnered with Grab to set up an AI lab with an initial investment of S$6million while NTU’s Data Science and Artificial Intelligence Research has attracted support from leading tech companies Nvidia and Paypal. With such big money backing the data science scene, it’s clearly a matter of time before talented data scientists start blossoming and match up to the expectations of the industry.

References :

Channel NewsAsia: Alibaba opens first joint research institute outside China


EDB: Singapore's big ambitions for big data in 2019


Forbes: Data science - What's the half life of a buzzword


HBR: Data Scientist, the sexiest job of the 21st century


KDnuggets: Data science vs machine learning vs business analytics  

Oreilly: Data Science terminology

Simplilearn: Data Science vs Big data vs Data Anaytics


Wikipedia: Data Science


A practice of gratitude - Thanksgiving at ConnectOne 2018

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A spin on the word thanksgiving as “thanks” and “giving” by Brisa, one of our interns led to this little reflection today. Although unintended but it was a powerful reminder that as the year closes on a high for us, that we have to be:

1)#thankful for all the joys and junks of the year

2)#giving of our time helping motivated individuals find meaningful jobs and startup founders raise human capital!

Personally, this must be a year where our small and humble beginnings have started to scale somewhat. Many have heard that it was a very rough first 2 years for us. But along came a few individuals who believed that we were motivated, able and with the right opportunity, will produce results. And we did. We are very thankful for them and for a wonderful community of talent and founders who along with them, believe in us.

Successful people have three things in common: motivation, ability, and opportunity
— Adam Grant, author of Give and Take

Last but not least, a toast to my co-founder, Fiona who supported my crazy idea back in 2013 to work with startups and continue to support more crazy ideas as we launch our new programs in 2019!

Cheers to all and wishing all of you a Merry Christmas and Happy 2019!!

All my best,

Elena Chow, Co-Founder of ConnectOne


As part of our party activity, we asked our key partners, clients and candidates what they are most grateful for this year and three words to sum up 2018. Below are the gathered thoughts and heartfelt reflections. May they act as a reminder for us to be thankful for the little things in life as well as inspire us to live with a greater purpose in 2019!

What are you most grateful for this year?

Grateful that investors trusted me enough to invest in my startup, which allowed me to commit 200%. No looking back now! Hired a highly qualified CTO, currently building a dedicated and eager team to kick-start things!
— Lius Widjaja, Founder and CEO of Gomodo Technologies Pte Ltd
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Grateful for health of loved ones and being able to have some family time
— Min Joo Yang, UI UX Designer
New season in life, country, job , experience as well as friendships
— Jen Lin, Head of Travel Platform
Opportunities to change, to grow, to influence and to help
— Bryan Long, Co-Founder and CEO of Stacck
For all the amazing members and partners I’ve met in the ecosystem. For those who has made an impact in my life through the positive sharing, knowledge transferred and the love and kindness
— Andee Chua, Head of Community of Found.
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Awesome company & colleagues, New home, New life partner
— Sabrinna Soh, Senior Consultant of ConnectOne

Three words to sum up your 2018

Tough, Challenging, Hope
— Terence Yow, Managing Director of Enviably Me Pte Ltd
Momentum, Validation, Empowering
— Lius Widjaja, Founder and CEO of Gomodo Technologies Pte Ltd
Transparency, Integrity,
Humility
— Jae Lee, CTO of Online Travel Platform
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Opportunities, Growth, Possibilities
— Jael Chng, Founder of My Working Title
Eventful, Clarity, Transitional
— Mindy, Head BD of Online Marketplace
AI, Evolution,
Re-examination
— Tomithy Too, Investment Manager of ST Telemedia
Fulfilling, Empowered, Inspired
— Michelle Quek, Community Manager of Found.
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Hectic, Hell, (But) Happy
— Kenny Lew, Senior Consultant at ConnectOne
Affirmation, Relationships, Great food and travels
— Pamela Tan, Consultant, Talent Community Lead of ConnectOne
Happiness, Laughter, Gratitude
— Yvonne Sia, Finance & Admin Lead of ConnectOne
ConnectOne Team

ConnectOne Team

 

Thank you for celebrating 2018 with us!

These are the things only founders over 40 can tell you

There’s a great romance about youthful founders. Startups must be full of adolescent dropouts who’re writing code, changing the world, and worrying about zits. You can hardly blame anyone for lionizing the young; Mark Zuckerberg, the preeminent founder of our time, launched Facebook when he was only 20 years old.

But the adoration doesn’t match reality. According to the Kauffman Foundation, a think tank focused on entrepreneurship, the average age for a successful startup founder is about 40 years old.

And a recent study (PDF link) from MIT, Northwestern University’s Kellogg School of Management, and the U.S. Census Bureau also found that the most successful entrepreneurs are middle-aged. They discovered that startups with growth in the top 1% of their industry had founders with an average age of 45.

The study found that correlation between success and age had a simple explanation: experience matters and older people have more of it.

Why experience is golden

Anna Gong, CEO of Perx Technologies

Anna Gong, CEO of Perx Technologies

It’s a perspective that Anna Gong, in her early 40s, CEO of Perx Technologies and a veteran of working with four previous startups in Silicon Valley, agrees with. “The mature executives have experience that’s immensely valuable. Back in my Silicon Valley days, many startups hired senior executives to help young founders scale and exit profitably.”

It’s all about execution, Gong says. “The startups we built that had traction were mostly run by seasoned executives who’d left companies like Intel, IBM, and Sun Microsystems. It’s not about if you dropped out of school, it’s about the management and the leadership. Experience is immensely helpful when guiding a growth stage company.”

How founders don’t have to take big risks

I have a risk-averse approach to entrepreneurship. I did it in my free time, which is a lot of work, but it’s something I recommend.
— Erwan Mace, Founder and CTO of Bitsmedia

But you don’t have to be a serial entrepreneur and eat ramen from age 20 to 40 to become an experienced founder. Erwan Mace was the VP of Technologies at Vivendi Mobile Entertainment, a large multinational corporation, before he moved back to Singapore. “I didn’t want to rush into a new job,” Mace says. “So in the meantime, I started a company.”

That was the birth of Bitsmedia, a startup that built apps for mobile. But two years into running Bitsmedia Google approached Mace with a job offer.

Erwan Mace, Founder and CTO of Bitsmedia (left) and  Nik Emir Din

Erwan Mace, Founder and CTO of Bitsmedia (left) and Nik Emir Din

“We were still small,” Mace recalls, “and none of our apps had really taken off. The Muslim Pro app had been launched the year before, and although it was showing some traction, it was still slow. So I joined Google, and in the evening and weekends, I continued working on Muslim Pro by myself.”

After a year at Google, Muslim Pro gained momentum, and at the age of 39 (editor’s note: close to 40!), Mace left Google to focus on Bitsmedia and Muslim Pro. “The decision was easy enough to make,” Mace says. “The revenue from Muslim Pro became equal to my salary at Google, so there was little risk. I have a risk-averse approach to entrepreneurship. I did it in my free time, which is a lot of work, but it’s something I recommend.”

But Mace was clear he didn’t start his own company just for the money. “I’m a hands-on guy,” he explained. “I had high-profile jobs, which meant less of that. I missed getting my hands dirty, creating something of my own. So no matter what, whether it was a viable business or not, I felt the need to work on my own stuff in my free time.”

What mindset can tell you about success

I distinguish between people with internal and external motivation.
— Hon Meng Moh, Co-Founder and Director of The RightU
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This internal drive is something Hon Meng Moh feels is essential for older founders. At 50, Moh has been a serial entrepreneur. He co-founded iFast Corporation at 31, which listed on the SGX in 2014. At 43, 45 and 47, he co-founded three more companies and has invested in several others.

“I distinguish between people with internal and external motivation,” Moh explains. A person who’s attracted by the image of being an entrepreneur, for example, or someone who wants to make a lot of money, is externally motivated.

“When the going gets tough,” Moh says, “and the going will really get tough, these guys are going to think of easier ways to make money. As opposed to people with internal motivation — entrepreneurs who are so passionate about an idea they can’t imagine doing anything else — who tend to persevere longer.”

This inner drive fuels the decisions an older entrepreneur will make. “For someone with internal motivation, age becomes less of a thing, and I find they’re able to take quite a bit of suffering.”

Hard-won wisdom from founders over 40

So what can founders and entrepreneurs of all ages learn from founders over 40?

Don’t do it for the money.

“A lot of people think it’s easy money because you keep reading about successful apps,” Mace says. “They couldn’t be more wrong. Only people with passion, a lot of work, and also a bit of luck, might turn a startup into a successful business. In most cases, it won’t be successful. But if you’re doing something you’re passionate about, you won’t be wasting your time.”

Build your network.

“The number of contacts is more important than your idea,” Moh says. “You can access capital and people from your contacts, so your network must be wide. If you sit there thinking your idea is great but you have no network and no money, I don’t think it’s going to do well. You’ll find that ideas aren’t worth that much, it’s whether you have the network and the capital to pull it off.”

Find the fire.

“I came from China to the US and struggled through all sorts of trials and tribulations,” Gong says. “You have to stand out from the rest, but how do you stand out when you’re a minority, female, and in tech; where there aren’t that many females? My upbringing taught me grit. For me, it’s about where you come from, what struggles you’ve experienced, and what’s that fire in your belly that makes you strive for excellence?”

Ever wondered what founders do after they they exit the startups they founded? The dreams, the challenges and the lessons?

Pictured from left: Benjamin Koellmann, Joelle Pang, Bryan Long and Audrey Low

Pictured from left: Benjamin Koellmann, Joelle Pang, Bryan Long and Audrey Low

Joelle Pang founded blog shop Dressabelle while she was working in a bank. She often worked 12 hours in the office, four hours on the blog shop, and slept for four hours before repeating it all again. It took her two and a half years before Dressabelle became profitable enough and she could quit her corporate job to work on it full-time. But that came with its own challenges.

“Dressabelle was my first startup and I became emotionally attached to it, my identity became attached to it,” Pang reflects. “I was so proud of myself when it was doing well, but on bad months I felt like a failure. I became overwhelmed and sank into depression. For a long time, I couldn’t get out of my house as I was physically, emotionally, and mentally burnt out.”

Thankfully, things ended positively for her. Dressabelle became successful and Pang eventually sold her shares. “It was the most challenging thing I went through but it was also the most centering event of my life. Your work should not dictate how you feel about yourself, the value of your life, and whether you are a success or a failure.”

These invaluable lessons are things you learn only after going through the fire of founding your own business. We spoke with Pang, who is now the regional business development director for FastJobs, Bryan Long, co-founder and CEO of Stacck, and Benjamin Koellmann, a co-founder of the HappyFresh Group, to discover things that only founders will know. The panel was moderated by Audrey Low, VP of Growth for ConnectOne.

The Problem is the Answer

Bryan Long’s mom told him to study hard, so he did. Long became a scholar, worked in the Ministry of Defense for six years and wondered if this was all life was about. At the age of 32, just as his second child was born, he quit his job.

Long did an MBA, went to law school, and then started Big Life Treats. “I did everything my MBA told me to do, I was on stealth mode and had a 40-page business plan. I launched it expecting a big crowd, but all I heard was crickets. I eventually closed the startup as it ran out of money.”

Long then co-founded Stacck, which automates communication between blue collar workers. Stacck is how he met Eduardo Saverin, one of the co-founders of Facebook.

“I remember his first question,” Long says. “It wasn’t about the product but rather, ‘Who is the customer and why is it a big problem?’ And I knew how to answer that as I did all the customer validation using Lean Startup techniques. We were ready with customer contracts and were able to raise money.”

Fit First, Scale Second

Benjamin Koellmann helped launch Lazada in Indonesia, seeing it scale from 50 orders a day to 10,000 a day. Even though it was an exciting time, Koellmann wanted to start a company he could call his own. He co-founded HappyFresh to work with retail chains and deliver groceries.

“Delivering the first order, seeing everything come to life, I remember that as a happy, proud moment,” Koellmann shares. “It took us five months from thinking we’re really going to do this to launching it.”

But there were struggles. A few months after launch, the team had promised investors they’d triple revenue over three months. “Scaling a business that hasn’t found the right product-market fit yet is unbelievably expensive. We hit the numbers, but they weren’t sustainable and it had lingering effects on our recovery. Had we been more moderate, things might have been different.”

Hiring is a two-way street

Joelle Pang didn’t trust anyone to take over her responsibilities at Dressabelle. “It was a mistake,” Pang says. “I ended up doing a lot of the execution and it took time away for strategic planning.”

Hiring is crucial to take a business to the next level, but an mis-hire can do as much damage as a right hire can do good. How did these founders get it right?

“When I hire, I look for self-driven people,” Koellmann says. “People who are independent, self-motivated, and flexible. In a startup, you do a lot of different things and sometimes you need to step up. You can be in marketing, for example, but will step in for ops because they need help. That flexibility is key.”

“Hire a bit different,” Long adds. “One way to test them is to hire the person as an independent consultant for a period of time.”

Pang concludes by saying that part of a hire’s performance also hinges on the founder. “The responsibility is on both the candidate and the founder. If a founder has mood swings, changes her vision every 3 months, or pivots continuously without a clear direction, you can imagine what it does to the morale of the company.”

Pictured from left: Benjamin Koellmann, Joelle Pang, Bryan Long and Audrey Low

Pictured from left: Benjamin Koellmann, Joelle Pang, Bryan Long and Audrey Low

Know When to Move On

Dressabelle was having a good run but Pang kept feeling like it wasn’t enough. “By financial standards, it should have made me feel like a success. But I kept thinking what my contribution to the world was. That led me to exit and sell my shares.”

Pang wanted to “do good through doing good business,” which she defines as solving everyday problems that benefit all members of society through technology and tech-enabled platforms. This led her to her current role as Regional Business Development Director of FastJobs, a non-executive job platform that aims to provide everyone with equal access to job opportunities.

“I always felt that I had to be an entrepreneur because I loved to be creative,” Pang says. “But I came to realize that I didn’t enjoy the administrative work. I enjoyed the creative process and I should turn that into something that creates real value. At FastJobs, it’s a great journey insofar as I do the launching, hiring across new countries and understand new cultures.”

How retail can thrive in the age of e-commerce: An interview with Love, Bonito’s Dione Song

In our exclusive interview with Love, Bonito’s first C-suite hire - Chief Commercial Officer Dione Song - find out what she has to say on why the firm made the surprising decision to open a brick and mortar store, despite its success in the e-commerce industry.