Sr. Data Scientist, Fraud Intelligence

Key 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
• Identify and model platform-specific abuse patterns, including referral fraud, promo stacking, cashback manipulation, purchase-and-return abuse, account takeover, and coordinated affiliate fraud
• Use frontier AI models as a force multiplier - compressing investigation cycles, automating workflows, and surfacing signals faster
• Build real-time and near-real-time scoring pipelines that deliver fraud risk decisions at the latency required to intervene before financial exposure is realized
• 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
• Mentor junior analysts in fraud modeling techniques and investigative thinking

Qualifications:  

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. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

• 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
• 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
• Strong communication skills - able to translate fraud signals and model outputs into clear recommendations for nontechnical stakeholders
• Familiarity with MLOps practices - model versioning, drift monitoring, and production deployment in a cloud environment
• Snowflake or equivalent cloud data warehouse experience
• TigerGraph database tooling is a plus

Minimum 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
• Snowflake or equivalent cloud data warehouse experience preferred
• Familiarity with graph database tooling, such as TigerGraph, Neo4j, or Amazon Neptune, is preferred

Five Principles for Success
Our worldwide practices describe specific behaviors that make Rakuten unique and united across the world. We expect Rakuten employees to model these 5 Shugi Principles of Success.

Always improve, Always Advance - Only be satisfied with complete success - Kaizen
Passionately Professional - Take an uncompromising approach to your work and be determined to be the best
Hypothesize - Practice - Validate – Shikumika - Use the Rakuten Cycle to succeed in unknown territory
Maximize Customer Satisfaction - The greatest satisfaction for our teams is seeing their customers smile
Speed!! Speed!! Speed!! - Always be conscious of time - take charge, set clear goals, and engage your team

Rakuten is an equal opportunity employer. Accessibility accommodations for candidates with disabilities participating in the selection process are available on request. Any information received related to accommodation needs of applicants will be addressed confidentially.

Rakuten would like to thank all applicants for their interest in this role however only qualified candidates will be shortlisted.

Beware of fraudulent job offers claiming to be from Rakuten. Rakuten does not send unsolicited job offers or request money during the recruitment process. Learn more: https://rakutenemploymentalert.com/

At the time of posting, Rakuten expects the Compensation (base salary + discretionary bonus) for this role to be within the range shown below. Individual compensation will vary based on job-related factors, including the skills, qualifications, and experience of the successful candidate as well as business need and geographic location. The successful applicant for this role will be eligible for stock options, health, vision, dental insurance, RRSP matching, Personal Time Off (PTO), Volunteer Time Off (VTO), and other employee benefits as the company implements.

CAD $107,957.00 - 157,957.00 annually