About Paidy Inc.

Paidy was founded with the mission to create a world of “We remove the barriers, embrace simplicity”, offering its real-time monthly consolidated credit service all across Japan.

Paidy started Japan’s first instant post-pay credit service for e-commerce consumers in October 2014. Paidy requires no pre-registration or credit card to use; Paidy consumers purchase products online using only a mobile phone number and email address (verification is established through a four-digit code via SMS or voice pin-code) and settle a single monthly bill for all their purchases, either at a convenience store, by bank transfer or auto-debit. Paidy also supports multi-pay installments and subscriptions. There are currently over 4,000,000 Paidy accounts in use (Oct 2020). Paidy has proved a powerful means of persuading first-time buyers to transact online. Its proprietary models and machine learning

mean that transactions are underwritten in seconds, with guaranteed payment to merchants.

Paidy increases merchant revenues by reducing incomplete transactions, increasing conversion rates, boosting average order values, and facilitating easy repeat buying.

For more information visit http://www.paidy.com.

Position Overview

Paidy is a fast-growing international start-up revolutionizing online payments in Japan. Paidy’s Risk & Analytics team supports decision-making and operations in all parts of Paidy’s business through data analytics and also designs the models and tools to reduce the company’s credit and fraud risk.

Paidy’s Risk & Analytics team is currently looking for a Data Scientist to improve its ability to support the growing business and to use user data to make smart strategic and automated decisions, especially about marketing and product strategy and development.

To be a successful member of the team, you should be highly adaptable, experienced analyzing user behavior data for an internet, e-commerce, or fintech company, excited to learn about diverse parts of Paidy’s operations, and eager to champion the use of data-driven business strategy.

Duties & Responsibilities

Work with stakeholders across Paidy in the style of an internal consultant who brings data science know-how and has a willingness to understand the stakeholder’s business perspective

Identify areas where the use of user behavior data – in ad-hoc analysis or as a machine learning solution – can help improve the marketing and product user experience function, and conduct the analysis/build the solution

Collaborate with stakeholders to define how to measure business performance, set up dashboards to track and report on the performance to stakeholders and executives

Work cross-functionally with risk department members on analysis of other business aspects that impact the user experience such as fraud and credit risk


Bachelor’s degree or higher, preferably in a quantitative field, or equivalent experience

2+ years work experience in a related role (data science, data analysis, business intelligence)

Experience working with common data science query and general languages (e.g. SQL + Python/R)

Experience with common machine learning tools (e.g. SKLearn, Keras, XGBoost), applying them to business problems aimed at improving the user experience of a web service

Experience working directly with business and product owners, translating technical findings from an analysis into simple findings and takeaways for a non-technical audience take a look at wording here

Experience working with Amazon Web Services, Google Cloud, or Microsoft Azure

Business English is required, Japanese skills are a strong advantage

What we offer

Flexible working environment in a fast-growing fintech company with modern technology stack in Tokyo

Analytically-minded, fast-paced and supportive team, inspired by agile ways of working

Opportunity to directly drive business results and clearly see how your work contributes to the business bottom line

Tagged as: agile, AI, Analytics, Azure, C++, Data, Data Analysis, Go, Keras, Machine Learning, Python, R, SQL


Job Overview
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