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Sr. Data Scientist, Fraud Intelligence
Rakuten (Rakutenrewards)
Toronto, CAN
Onsite
$107,957 to $157,957,
Discovered 2 weeks ago
Fraud detection modelingMachine learningSupervised classificationAnomaly detectionBehavioral scoringSQL
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Fraud detection modelingMachine learningSupervised classification
Role Overview
Join Rakuten Rewards Trust & Safety to protect the platform, merchant partners, and members from fraud and abuse.
Own the fraud detection lifecycle from exploratory analysis and behavioral investigation through production machine learning deployment and monitoring.
This is a high-impact, lead-leaning individual contributor role focused on reducing financial loss and protecting the rewards experience.
Key Skills for This Role
Fraud detection modelingMachine learningSupervised classificationAnomaly detectionBehavioral scoringSQL
Full Job Posting
Role overview
Join Rakuten Rewards Trust & Safety to protect the platform, merchant partners, and members from fraud and abuse.
Own the fraud detection lifecycle from exploratory analysis and behavioral investigation through production machine learning deployment and monitoring.
This is a high-impact, lead-leaning individual contributor role focused on reducing financial loss and protecting the rewards experience.
Core responsibilities
- Design and deploy classification, anomaly detection, and behavioral scoring systems across account creation, transactions, redemption, and referrals.
- Model referral fraud, promotion stacking, cashback manipulation, purchase-and-return abuse, account takeover, synthetic identity, affiliate fraud, and coordinated rings.
- Use frontier AI models to accelerate investigations, automate workflows, and surface signals.
- Build real-time and near-real-time fraud risk scoring pipelines.
- Create model validation frameworks covering precision-recall analysis, threshold optimization, A/B testing, and champion-challenger testing.
- Manage machine learning models and rules engines in fraud decisioning.
- Build automated triage workflows and lead incident response and root cause analysis.
- Develop fraud KPI dashboards and communicate findings to senior and executive stakeholders.
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