Rakuten Rewards
Sr. Data Scientist, Fraud Intelligence
Toronto, Canada · Senior
Sponsorship not specified$108k-$158kDetected 31 days ago
PythonSQLSnowflakeCloud PlatformsMachine LearningData AnalysisData ScienceNLPMLOpsStatisticsA/B TestingDetection EngineeringIncident ResponseAffiliate MarketingCommunicationRisk Modeling
About the role
- You will work across every dimension of member-facing fraud and abuse, including referral gaming, promo stacking, cashback manipulation, purchase-and-return abuse, account takeover, synthetic identity, affiliate fraud, and coordinated ring behavior.
- This role is for data scientists who default to AI-first.
Responsibilities
- Design and deploy end-to-end fraud detection systems - supervised classification, anomaly detection, and behavioral scoring - across the full member lifecycle from account creation through transaction, redemption, and referral
- Design model validation and testing frameworks - precision/recall analysis, threshold optimization, A/B testing, and champion-challenger testing - to keep detection accurate as fraud patterns evolve
- Manage the interplay between ML models and rules engines, knowing when a hard rule is more appropriate than a probabilistic score
- Build automated fraud triage workflows that reduce manual investigation queues and scale team capacity
- Own incident response - investigation, root cause analysis, and rapid model or rule adjustments to contain exposure in real time
- Develop fraud KPI dashboards and present findings clearly to senior and executive stakeholders
- Partner with Product, Engineering, Compliance, and Finance to embed fraud controls proactively
- We create products and services that provide exceptional value by aligning members and the businesses that want to engage them in a shared community.
Requirements
- 5-7 years of relevant work experience required
- Bachelor's Degree in Statistics, Mathematics, Computer Science, Economics, or a related quantitative field required
- Background in fraud detection, trust & safety, risk modeling, or abuse prevention required
- Experience in e-commerce, fintech, digital rewards, affiliate marketing, or payments platforms required
- To perform this job successfully, an individual must be able to perform each essential duty satisfactorily.
- The requirements listed below are representative of the knowledge, skill, and/or ability required.
- Proven model testing and validation experience - precision/recall trade-offs, threshold calibration, A/B and championchallenger experimentation
- Experience working with rules engines alongside ML models in a fraud decisioning context
- Experience with graph-based or network fraud detection to identify fraud rings or coordinated abuse
- Familiarity with MLOps practices - model versioning, drift monitoring, and production deployment in a cloud environment
- Active, demonstrated use of frontier AI models in professional work - able to articulate specific examples where AI accelerated analysis or automated a workflow
- Hands-on experience building and deploying fraud, risk, or abuse detection models in production - classification, anomaly detection, or behavioral scoring at scale
- Strong SQL & Python skills across feature engineering, model development, pipeline construction, and workflow automation
- Strong communication skills - able to translate fraud signals and model outputs into clear recommendations for nontechnical stakeholders
- Snowflake or equivalent cloud data warehouse experience
Nice to have
- Snowflake or equivalent cloud data warehouse experience preferred
- Familiarity with graph database tooling, such as TigerGraph, Neo4j, or Amazon Neptune, is preferred
- TigerGraph database tooling is a plus
Compensation
- CAD $107,957.00 - 157,957.00 annually
Benefits
- At the time of posting, Rakuten expects the Compensation (base salary + discretionary bonus) for this role to be within the range shown below.
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