Director, Data Analytics - Risk & Fraud

Rakuten Viber is one of the most popular and downloaded apps in the world. Working with us provides a unique opportunity to influence hundreds of millions of our users and to be part of the journey that makes us a super-app. Our mission is to make people’s lives easier by enabling meaningful connections, from precious moments with family and friends, through managing business relationships to pursuing their passions.

As a Director in Analytics, you will work in a highly collaborative environment with extensive amounts of data to research and develop deep learning models to solve real-world problems and apply them to tasks such as identifying bad actors, preventing fraud, building anomaly detection models, and analytics at a high scale.

As a senior manager, you are expected to create an alignment across different divisions, focus on strategic business KPIs and lead other managers to collaborate and perform shared goals. Successful outcomes in this role will significantly impact the business.

Responsibilities
Lead the development and optimization of spam and fraud detection systems using machine learning and rule-based engines.
Work closely with management, product, engineering, compliance, legal, and security teams to align, present, and implement end-to-end fraud solutions.
Ensure adherence to KYC, AML, and other financial regulations while managing fraud risks.
Leverage the extensive data received from our application to enhance model performance and accuracy.
Requirements
7+ years of experience in hands-on working on spam and fraud problems at a scale of at least 1MM transactions/events per day, deployed solutions to production with a proven impact.
3+ years of experience in managing Spam, fraud prevention and risk teams at a corporation, preferably in fintech or cyber-tech companies with a proven business impact.
3+ years of experience in Python, SQL, and AWS cloud. Ability to write readable and maintainable code.
Master’s degree in Statistics, Finance, Data Science, or Computer Science.
Advantages
Background in data science or cybersecurity with a focus on spam and fraud.
Proven track record of reducing fraud and spam actors at scale, with strong type-1 and type-2 error estimates.
Strong understanding of hypothesis testing and RCT. Background in applied statistics.
Working in high scales of >10MM transactions/day.
Experience working with technologies like Athena/Trino, Spark, AML, CI/CD, and Tableau.