Data Analyst: Providing the Best to Users from the Data of 50 Million People

This Professionals series showcases talented experts who support PayPay Group’s operations.
In this issue, we interviewed Shin-san, a data analyst who supports data-driven and speedy decision-making in the company’s financial business. We asked why chose PayPay and about the unique and rewarding aspects of working here.

Desire to See the Life-Changing Service Evolve as an Insider

Please tell us why and how you joined PayPay

The reason I switched jobs was because I wanted to be involved in a service that I actively use in my daily life.
It is very important to have the user’s perspective in consumer analysis. However, in my previous job in the ad network and in the e-book industry, I acutely felt my limits as an analyst because I could not analyze deeper since I was not using those services every day as a user.

I have always been a heavy PayPay user and PayPay has changed my life. PayPay was released the year I entered the workforce, and I’ve been watching its growth ever since. Now we can use PayPay wherever we go, and in another five to ten years, I am sure PayPay will achieve things we can’t even imagine now. I wanted to experience that evolution as an internal member.

During the interview with Yanase-san, our Division Head, I could sense the passion of my would-be colleagues to make the world happier through PayPay’s services. Don’t you think it would be fun to work with people like that? Ultimately, I’d say that was the most decisive factor.

What was your impression when you first joined PayPay?

Even though PayPay is a financial company, I felt it was indeed a fintech company because its quick decision-making process and data-driven culture were at the level of IT companies. I was thinking that PayPay, while claiming to be data-driven, actually only uses data as a minor reference for making choices. It is rather common for IT companies to have an analytical environment but not utilize it for decision-making. However, PayPay makes 9 out of 10 decisions based on data. It is very rewarding as a data analyst to know that my work is helping to make timely and data-driven decisions.

Data Usability Leads to Service Growth

What does the Data Science Team do?

As for routine work, KPI management is our main task. We manage the entire process of selecting the most appropriate KPIs, processing and designing the data sources while considering their stability for daily distributions, and using BI tools to visualize each indicator on dashboards.
Our main work in a project is insight analysis to both understand users and support decision-making. When considering new services and new measures, PayPay’s vast amount of payment and behavioral data are used to quantify and verify the hypotheses of persons in charge.

One example is a cross-use analysis of the mini apps “Earn Points” and “Invest.” With the addition “Invest,”, we are monitoring users’ usage and behavior patterns, including how the number of users and investment amounts were divided or added between the two mini apps.

Of course, in addition to responding to a given hypothesis, the Data Science Team may also find patterns by exploring the data and make suggestions. I would like to discover the thoughts and intentions of users hidden in the data and contribute to providing better services to users as a data analyst.

What do you value in your work?

To ensure that members in the business side of our operations do not get into trouble. Data is meaningless unless people use it. We also backcast delivery dates based on when they will be used, and our dashboards are designed first and foremost to be easy to read for business members.

I also tell my team members to try to explain things as clearly as possible without using jargon, and to focus on what insights they can use now rather than on technically advanced things.

As a user, I am motivated to make PayPay’s services more all-encompassing and easier to use. To that end, I want to first help the business members around me and get them to say, “I am glad to have the Data Science Team.”

What is the atmosphere of the current team?

The Finance Business Strategy Department as a whole has strong teamwork and each member is willing to help each other.
The Data Science Team currently consists of four people, including myself. As a leader, I aim to create an environment where members can work while consulting with each other at any time. Since a narrow perspective reduces the quality of our analyses, we communicate with each other for at least one hour every day, even while working from home, so that we can analyze from various perspectives. In addition to talking on Zoom and Slack, we may also gather in the office for intensive work, such as discussing issues that cannot be resolved remotely or that require more active discussion throughout the day, or reviewing each other’s work.

Another unique aspect about us is that my team and the Business Team are quite close. Sometimes we join discussions from the decision-making phase and conduct surveys, and both teams work in consultation with each other at any time. The Data Science Team constantly receives information on business issues and share the results of quantitative verification of hypotheses with the Business Team. Moreover, the Business Team’s ability to hypothesize is amazing, so we are never lacking in subjects to analyze.

Recently, we have been holding study sessions on data analysis. Everyone is very active and asks questions; some have even asked for the video recordings so they can review the sessions. That’s because we all understand the importance of data analysis. As a data analyst, I find it a very easy and motivating environment to work in.

Gaining Insights Previously Unheard Of

Is there anything you would like to accomplish in the future?

Our vision and mission as the Data Science Team is to create an environment where there is not one single problem related to data analysis. We want to eliminate data that we want to see but can’t, and hypotheses that we want to verify but can’t. Furthermore, I would like to visualize areas that no one was mindful of. There may be important insights in areas that business members take no notice of, so I would like to increase the frequency of us the analysts initiating the conversation.

Finally, do you have a message for potential candidates?

I think PayPay is the perfect environment for data analysts who want to experience a diverse user base, a large amount of data, and a faster PDCA cycle. The demographics of PayPay users are well balanced, and the environment is very attractive in terms of all the data segments that are available.

For me, PayPay is something that I can grow alongside with. I feel like the company is supporting my growth just as much as I am supporting PayPay’s growth. There is abundant support for the environment, including the systems used by data analysts, and a culture that encourages technical challenges and growth, like participation in conferences.

As a team leader, I also want to build a team where each member can support each other’s growth. Why not give PayPay a try? We can work together and grow as data analysts every day!

*The recruitment status is current at the time of the interview.

Special Thanks: Heejae Shin / Editor: Kaoru / Author: PayPay Inside-Out Editorial Team / Photographer: Tak
*Employees’ affiliations are as of the time of the interview.