Data Scientist - Fraud Analytics

6w1 month ago

Paidy Inc.

Tokyo, JP · Full-time

About this role

Paidy is Japan's pioneer and leading BNPL service company that uses proprietary models and machine learning to underwrite transactions in seconds. The Fraud Risk Department is looking for a Data Scientist to help combat fraud within the Paidy payment ecosystem using payment and consumer behavior data to identify fraudulent patterns.

This role involves designing and maintaining real-time fraud detection and alerting systems that are efficient and scalable. You will develop and fine-tune models to identify fraudulent behaviors, analyze complex fraud patterns, and produce detailed reports for senior management. You will also coordinate cross-functionally with Engineering, Fraud Operations, Product, and Marketing teams.

To be successful, you should be highly adaptable with past achievements in financial, e-commerce or telecom industries. The fraud team uses a keen eye for detail and out-of-the-box thinking to set rules and prevent losses. You will act as a primary liaison with external parties and vendors to enhance the fraud ecosystem.

You will build deep fraud domain knowledge and stay up-to-date with the latest industry trends and emerging threat vectors. You will provide actionable feedback on product designs to ensure they are fraud-resistant while maintaining a frictionless user experience. This role offers the opportunity to drive data-driven improvements and advocate for resources to strengthen fraud defenses.

Requirements

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.
Highly adaptable with demonstrated past achievements working in financial, e-commerce, or telecom industries.
Experience designing or maintaining real-time fraud detection and alerting systems.
Knowledge of machine learning models for identifying fraudulent behaviors and patterns.

Responsibilities

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.
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.