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About Paidy Inc.
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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 was acquired in September 2021 by PayPal, the global payments company. Paidy continues 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.
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About Position
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Join our Fraud Analytics team, where you’ll play a critical role in maintaining the security of our seamless checkout process. We believe in offering our customers a frictionless experience—during checkout, they only need to provide an email and phone number to instantly access a credit account and have their payments underwritten. It’s fast, efficient, and convenient, but it comes with the challenge of ensuring that fraud is detected and prevented in real time.
As a Data Scientist in this team, you will work alongside fraud risk experts to develop solutions that stay ahead of emerging fraud patterns. You’ll leverage technologies, including AWS, Glue, Spark, and EMR, to build monitoring systems and deploy alert mechanisms that respond instantly to suspicious activities. Your insights and models will directly influence our ability to protect both the business and our customers, ensuring that every transaction is secure without compromising the speed and simplicity of our checkout.
If you are excited about using data to solve complex challenges and want to make a real impact in a dynamic environment, this role is for you.
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Key Role and Responsibilities
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- Design, create, and maintain real-time fraud detection and alerting systems that are efficient, scalable, and capable of handling high transaction volumes.
- Develop and fine-tune machine learning models that detect fraudulent behaviors, leveraging vast amounts of data to ensure accuracy and precision in predictions.
- Analyze patterns, produce detailed reports for senior management in fraudulent activity and implement proactive countermeasures to prevent future incidents and reduce false positives.
- Collaborate with cross-functional teams, such as Engineering, Fraud Operations, and Product teams, to ensure seamless integration of fraud rules, models and tools into the wider fraud detection, alerting and prevention framework.
- Provide actionable feedback on product designs to make them more fraud-resistant, ensuring that security is integrated into the development process.
- Innovate new tools and techniques that improve the team’s efficiency in monitoring, alerting, and preventing fraud, enabling faster response times and better risk management.
- Monitor and assess the performance of existing fraud detection systems, making data-driven improvements to adapt to evolving threats and trends.
- Document processes and methodologies for transparency and knowledge-sharing within the team, contributing to a culture of continuous learning and improvement.
- Stay up-to-date with the latest advancements in fraud detection technologies and data science practices, bringing new ideas and approaches to the team.
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Skills and Requirements
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- Proficiency in essential data science tools such as SQL, Python or R, with experience in data manipulation and analysis.
- Experience with machine learning frameworks and libraries (e.g., Scikit-learn, or similar).
- Familiarity with cloud platforms, particularly AWS services like Glue, EMR, and other data processing tools.
- Strong understanding of data visualization tools (e.g., Tableau, Looker, or similar) for reporting insights would be a plus.
- Excellent written and verbal communication skills in both English and Japanese, with the ability to present complex ideas clearly to technical and non-technical stakeholders.
- Previous experience in a data science or analytics role, particularly in fraud detection, financial services, or e-commerce environments would be a huge plus.
- A proactive mindset and a passion for leveraging data to drive business decisions and improve fraud prevention strategies.
- Ability to deliver under pressure and demonstrate a sense of urgency when required.
- Paidy team will ask about your user experiences with Paidy Apps during the interview. Please download Paidy App and try it out!
For those who are not able to download 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.
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What We Offer You
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- Diversified team with 238+ colleagues from 42+ countries
- Exciting work opportunities in a rapid-growing organization
- Cross-functional collaboration
- Flexible work-from-home arrangement
- Competitive salary and benefits
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Paidy Values
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Be a winner / 勝ちにこだわる
- 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
Own and deliver, together / 共に結果を出す
- 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
Be a valued team member / 価値を認められるメンバーになる
- 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
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