Having a strong Data team is an important part of any fintech company, like at October. The Data team formed two years ago and is based in the Amsterdam office. This team is responsible for setting up the infrastructure, performing analyses and deployment of models, and providing decision support to other teams. We met with Tejas Sherkar, Lead Data Scientist and Zheya Feng, Junior Data Scientist.
An international background
Tejas Sherkar
Tejas: “After a bachelor’s degree in Energy Science & Engineering at IIT Bombay, I obtained my PhD in Applied Physics at the University of Groningen. I started my career as a Data Scientist at one of the biggest payment platforms. I made the move to October last year, where I lead the Data team.
Zheya: “I have a bachelor’s degree in E-business from a Chinese University in Zheijiang. In addition to this I have a master’s degree in data science from the University of Amsterdam. I built data models for ranking and recommending restaurants for tourists as an intern in the largest online travel agency in China. Because of my work within multiple sectors and disciplines, I am able to think from multiple perspectives when solving a problem”.
The importance of a Data Team
Zheya Feng
Tejas: “The use of data is not new to fintech companies. But data science goes a step further to help us investigate and understand complex behaviors and trends in data. At October, we are able to draw lessons from the data we have collected over a number of years. We learn from this data to conduct automated risk analysis, fraud detection, customer acquisition and various product improvements. Zheya adds to this: “Thinking from a data science perspective can be applied to any data field and with advanced models we gain better insights than traditional methods. These results help us improve not only the October portfolio but also the user experience.
Proud of the Magpie scoring model
Tejas: “At October we get the chance to solve difficult problems with creativity and ingenuity. Zheya agrees: “Every day, more and more data comes in that enables October to leverage its value. During our team discussions, we bring in different ideas and it’s exciting to validate these ideas with the available data. “For example, over the past few years we have been working hard on an automatic scoring model for funding requests called Magpie, “ Tejas continues. “Magpie is built using machine learning algorithms and large amounts of data, which we have collected over the last 5 years in all countries where October is active. And this model also improves as we collect more data and apply new insights”.
Data science inspiration
Which companies are an inspiration for the data scientists of October? Zheya chooses the Chinese internet company Meituan Dianping. “This company provides food delivery, ticket booking and many other online services. They build great systems for retrieving information and making recommendations to customers with a huge amount of data on streaming text, images and user behavior and they distribute their approach as an open source”. Tejas: “Swedish company Spotify, known for their music streaming service. They have developed some of the best recommender systems ever built. It’s not just the vast amount of data that helps them, but their culture of putting their user at the center and understanding their needs and pain points. They’ve managed to make data their most important asset in scaling their business to new heights.
Want to be a part of the Data team at October? Have a look at the October job site.