Michal Polanowski is the head of Gojek’s Data Science Financial Services team.
Michal Polanowski is the head of Gojek’s Data Science Financial Services team.

“We exist because of data,” says Michal Polanowski.

Michal is a Polish data scientist and the head of Gojek’s Data Science Financial Services team.

Gojek is an Indonesian startup; a technology company with operations in Indonesia, Singapore, Thailand and Vietnam. It is also a decacorn – a startup with a valuation of at least $10 billion. At the time of writing, Gojek’s Singapore operations focus solely on ride-hailing, while its overseas operations provide services such as food delivery, mobile payments, general logistics, financial products like loans, and more.

Michal and his team play an important role in the heart of the Gojek “Super App”, which has over 20 services. They oversee Gojek’s financial services for customers, drivers, and merchants. As part of that, they build models to predict attrition rate, pricing and adoption. Adoption models are models that seek to predict if an individual will accept a particular service. Michal’s team also runs a risk analysis of users who take up loans from Gojek. This is crucial to Gojek’s PayLater service, which provides a short-term, 30-day lending service that is available to Indonesian users approved by Gojek.

Before launching this service, Michal and his team had to way finds to assess the creditworthiness of borrowers. This means ploughing through data such as a user’s transaction history.

“Based on our current data, we identified two types of users”, Michal says. “One who has been making orders and working with Gojek for many years, versus another who has recently created an account and has not been making any orders or large payments."

By analysing this information, Michal and his team can identify whether a particular user is genuinely interested to use Gojek’s services or has created an account for potentially fraudulent reasons.

However, this is sometimes more art than science, as it could simply be a case of a new individual joining the Gojek platform, so more time might be required to evaluate the user’s transaction history. Thus, the more data they have, the better they can make predictions, Michal explains.

Michal’s work becomes more challenging when there is a lack of quality data. He explains: “In Indonesia, a lot of people don’t use financial services or even have a savings account, so their financial footprint is non-existent in the traditional (banking) meaning.”

To tackle this problem, Michal and his team utilised data from alternative sources – information such as the length of time an individual has been a Gojek user, and the type of services that he or she uses - before they can develop their first version of a prediction model.

The work did not end after the launch of PayLater; Michal says the project is “ongoing”, as the team constantly receives feedback which they will use to finetune their services.For example, when the team noticed that some users had difficulty understanding how to make repayments on the app, they quickly got in touch with the users for their feedback, and re-designed the user interface to make the repayment process intuitive and seamless.

“We are constantly improving based on feedback from our users. We really want to make sure that our users feel that they are fairly treated,” Michal says.

Life as a data scientist

While Michal and his team managed to resolve most challenges for the PayLater project, there were times when even their best efforts did not work.“Results are not always guaranteed. Just because we have data and a problem, it does not mean that we can build a good model to solve that problem. Sometimes, the connection between the problem and data is just not there,” he shares.

A model, which is a mathematical or statistical relationship between different variables, is essential for developing digital solutions at Gojek. But contrary to popular belief, data scientists do not spend most of their time building models.

“When taking a data science course, it is easy to believe that 90 per cent of your time as a data scientist will be spent working on model creations and optimisations. In reality, about 80 per cent of your time will be dedicated to data collection, transformation, and evaluation or exploration. Maybe only 10 per cent of your time will be used for model creations and optimisations,” Michal says.

Additionally, data science projects are not completed overnight. This is unlike the Hollywood idea of a data science genius, who suddenly develops solutions in a moment of inspiration, Michal says. He points out that patience and persistence are the “secret sauce” in this job: “A proof of concept model can be created fairly quickly in a matter of hours or days. But a proper model testing and deployment can take weeks or months depending on the complexity and the number of iterations.”

And while some have an image of data scientists as bookish or “numbers people”, this is sometimes a hollow stereotype.

From basketball player to data scientist

Michal did not set out to become a data scientist. In fact, he wanted to be a professional basketball player.

“When I was in Poland, I was fortunate enough to be on the national team. When I was around 20 years old, I suffered a major knee injury. That gave me the time to reflect on what I wanted to do,” he recounts.“I got my undergraduate, masters and doctorate degrees from the US. I had originally planned to work in academia. However, during my doctorate studies, my wife suggested I try working in the industry first before deciding on whether to work in academia,” he adds.

Armed with a Bachelor of Computer Science, an MBA in Business Administration, and a PhD in Financial Planning, Michal joined food company Delhaize America as a business intelligence analyst after graduation. After a two-year stint, he moved on to Walt Disney’s advanced analytics team.

“Disney was an opportunity to see how big data can be used. Information such as the way people book hotels and the time spent in the theme parks can be used to plan logistics across the different theme parks which serve up to 100,000 visitors per park.”

After Walt Disney, Michal moved to Singapore and joined e-commerce company Lazada as a data scientist. Then, he joined Gojek.

Benefits of working in Singapore

According to Michal, working in Singapore has been a pleasant experience.

“In terms of work, Singaporeans are extremely professional, punctual and they get things done. It gives me a lot of pleasure to work here as everyone has this internal drive, high work ethics, and a sense of camaraderie. From the start, Singaporeans accept you. Slowly, your colleagues become your friends.”

He also notes that Singapore is a hub for many big companies, and it would be tough to find a Fortune 500 company that does not have an office here.

As a data scientist and a hiring manager, working in Singapore offers plenty of benefits.

“Singapore has many extremely skilled data scientists. Thanks to some top schools with a very rigorous curriculum, we get highly skilled recruits each year that can contribute from day one.”

“Also, the government has many programmes that help companies with hiring data scientists and further increasing their skills. Singapore also hosts many international conferences, training centres, and boot camps which allow for the quick levelling-up of one’s skills and keeping up with industry trends.”

Additionally, one need not worry about the common anxieties associated with working abroad, because Singapore is a safe place for raising children, with “super-efficient infrastructure, very transparent laws and a friendly government,” says Michal.

In addition to these benefits, Michal’s favourite part about working in Singapore is the food.

“It is impossible to find another place on earth with so many types of cuisines. Within one hawker centre, I can get world-class Chinese, Indonesian, Malay, and Indian food,” he shares.

Getting hired at Gojek

For Michal and his colleagues, working at Gojek offers plenty of perks. For instance, there are no official working hours. Neither is there a dress code. Employees are also offered unlimited sick leave and vacation.

The good news is Gojek is expanding rapidly, so they are hiring for various roles ranging from data scientists and programmers to engineers and product managers.

Gojek Singapore’s General Manager Lien Choong Luen, who is responsible for the company’s commercial operations and other business activities in Singapore, shares what it is like to work at the startup.

“Gojek is a big startup that is still growing. As the company expands, we have to find new ways to solve issues, so it is not a steady-state company where there is a job role to solve a specific issue.”

“The main point is that the box is growing, and everyone needs to pivot and take on new roles and what excites them. This is what I tell my team when I try to recruit them: if they like ambiguity, being curious and taking on more, Gojek is a great place for you.”

For fresh graduates keen to join Gojek as a data scientist, Michal has some tips.

“You need to have your own projects. The projects don’t have to be amazing, but they should show your initiative beyond the usual coursework. It really makes a difference during a work interview as it shows how much interest you have in the topic, instead of just broadly saying you are interested in data science.”

The Gojek hiring process for data scientists is rigorous. It starts off with a curriculum vitae screening. After the screening, selected candidates will be given a dirty data set and asked to build a credit score as an assignment, for example.

Those who pass the assignment will have to do a 20-minute presentation and go through a 25-minute interview by the hiring team, where candidates are assessed based on their fit with the organisational culture. Thereafter, successful candidates will be given a two-hour standardised interview where they are tested on statistics, mathematics, reasoning, and Standard Query Language (SQL).

Michal sums up his work at Gojek: “We solve challenging problems. Often, the problem we solve is novel, and there is no answer on the Internet. For people who love riddles and enjoy being challenged, this is a dream place to work. You definitely won’t get bored.”

Why Singapore’s Infocomm industry is the next big career opportunity

Even in the early 2000s, the growth of ecommerce hinted at the coming digital revolution. But over the past decade, the growth in the infocomm industry – along with attendant demand for digital professionals – has grown exponentially.

On the private hire vehicle scene, Grab and latent competitor GoJek have emerged as major transport players, within the last five years. In finance sector, the growing demand for online banking, eWallets, and other secured transactions have fuelled a massive demand for cybersecurity experts. In addition, Singapore’s Smart Nation initiative has seen a push for SMEs to go digital, fuelling demand for infocomm professionals at multiple levels – from the smallest start-ups, to companies that are rapidly scaling up.

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