Data Scientist - Fraud Analytics

Paidy is Japan's pioneer and leading BNPL service company. At Paidy, we believe in creating simple, instant experiences to take the hassle out of shopping with a touch of magic.

Paidy offers instant, monthly-consolidated credit to consumers by removing hassles from payment and purchase experiences. Paidy uses proprietary models and machine learning to underwrite transactions in seconds and guarantee payments to merchants. Paidy increases revenue for merchants by reducing the number of incomplete transactions, increasing conversion rates, boosting average order values, and facilitating repeat purchases from consumers. 

Paidy has reached an agreement to join PayPal, the global payments company. Paidy will continue to operate its existing business, maintain its brand and support a wide variety of consumer wallets and marketplaces by providing convenient and innovative services.

Paidy continues to innovate to make shopping easier and more fun both online and offline. For more information, please visit http://www.paidy.com. 

Paidy’s Credit Risk and Fraud Risk departments support 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. The Fraud Risk Department is currently looking for a Data Scientist to help combat fraud within the Paidy payment ecosystem. The fraud team’s role is to use payment and consumer behavior data to identify fraudulent patterns, understand how bad actors are abusing Paidy and set rules to prevent losses. 

To be a successful member of the team, you should be highly adaptable and can demonstrate past achievements working in the financial, e-commerce or telecom industry. This position requires somebody with a keen eye for detail and an out of the box way of thinking. 

• →Design and maintain real-time fraud detection and alerting systems that are efficient, scalable, and capable of handling high transaction volumes.
• →Develop and fine-tune models to identify fraudulent behaviors, leveraging large datasets to ensure high accuracy and precision.
• →Analyze complex fraud patterns and produce detailed reports for senior management to implement proactive countermeasures and reduce false positives.
• →Use strong presentation skills to report on work impact and advocate for the necessary resources and budget to strengthen Paidy's fraud defenses.
• →Coordinate cross-functionally with Engineering, Fraud Operations, Product, Marketing, and PR teams to ensure a unified approach to fraud prevention.
• →Act as a primary liaison with external parties and vendors to identify, evaluate, and hire new data sources or specialized tools that enhance our fraud ecosystem.
• →Provide actionable feedback on product designs to ensure they are fraud-resistant while maintaining a frictionless user experience.
• →Build deep fraud domain knowledge and stay up-to-date with the latest industry trends and emerging threat vectors.
• →Monitor and assess the performance of existing detection systems, making data-driven improvements to adapt to evolving trends.
• →Document processes and methodologies to ensure transparency and knowledge-sharing within the team.

• Proficiency in essential data science tools such as SQL and Python or R, with experience in data manipulation and analysis.
• Previous experience in a data science or analytics role, particularly in fraud detection, financial services, or e-commerce environments.
• Proven ability to translate technical findings into simple, persuasive takeaways for non-technical stakeholders to secure buy-in for new initiatives.
• A proactive mindset with a strong interest in building specialized fraud domain knowledge and driving business decisions through data.
• Ability to deliver high-quality work under pressure and demonstrate a sense of urgency when reacting to fraud attacks.
• Bachelor's degree or higher 
• Minimum business level English skills (including speaking and writing).

• Excellent written and verbal communication skills in both English and Japanese (Business level or higher) to coordinate effectively with internal teams and external partners.
• Experience with machine learning frameworks (e.g., Scikit-learn, XGBoost), cloud platforms like AWS (Glue, EMR), and building AI-driven models for scalable underwriting/detection.
• Bachelor's degree or higher in a quantitative field (e.g., Mathematics, Statistics, Economics) or equivalent professional experience.

The Paidy team will ask about your user experiences with the Paidy App during the interview. Please download the Paidy App and try it out!

• iOS: https://apps.apple.com/jp/app/paidy/id1220373112
• Android: https://play.google.com/store/apps/details?id=com.paidy.paidy&hl=en&gl=US

For those who are not able to download the Paidy App, due to the regional restrictions, please be advised that you download the similar App, such as Klarna, Afterpay, Affirm and so forth, and come up with your opinions on these applications and services.

Please note that you must be eligible to work in Japan.

• Always seek to beat expectations. / 期待値を超える為に常に努力する。
• Display surprising speed and resourcefulness. / 人をスピードと機知で驚かす。
• Overcome weaknesses by leveraging the strength and help of others to win. / 仲間の強みを活かしたり協力を得ることで、自身の弱みや足りない点を克服する。

• Fully support the final decision even if at times you may disagree. / たとえ意見が対立することがあったとしても、最終決定を全面的に受け入れ支持する。
• Acknowledge and gather the power of others, by communicating and collaborating with them. / 仲間の力を認めて活用し、積極的にコミュニケーションをとり、協力する。
• Show a will to own actions and go the extra mile without being asked. / 行動について強いオーナーシップを持ち、言われずとも業務を遂行しきる覚悟を持つ。

• Strive to play an integral role. / 替えの効かない役割を果たす。
• Embrace and bridge differences in perspective, language, and culture. / 異なる意見・考え方、言語と文化の架け橋になる。
• Don’t compromise - raise the bar for yourself and others. / スタンダードを上げ続けることに妥協しない。