Job Description:

Rakuten International is a division of Rakuten Group, Inc., a Japanese global technology leader in services that empower individuals, communities, businesses, and society. Headquartered in San Mateo, California with more than 4,000 employees worldwide, the Rakuten International business portfolio includes market leaders in e-commerce, digital marketing, advertising, communications and entertainment. We create products and services that provide exceptional value by aligning members and the businesses that want to engage them in a shared community.

Rakuten is the most rewarding way to shop, giving millions of members Cash Back when they buy from their favorite brands. As a leading shopping platform, Rakuten partners with thousands of top brands across apparel, beauty and wellness, grocery, travel, on-demand services, subscriptions, and dining, helping members save on everyday purchases. Since 1999, Rakuten members have earned more than $4.6 billion in Cash Back, making it the largest Cash Back platform of its kind. Learn more at Rakuten.com.

Job Summary:

The Senior Data Scientist, Fraud Intelligence, sits within the Rakuten Rewards Trust & Safety function and is responsible for protecting the platform, its merchant partners, and its members from the full spectrum of fraud and abuse. This role owns the end-to-end lifecycle of fraud detection - from exploratory data analysis and behavioral investigation through to building, deploying, and monitoring production-grade machine learning models that operate in real time. 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. Using frontier models (Claude, Gemini, GPT-4 class) to drive efficiency is an expectation here, not a perk.** We want people who reach for AI before a manual process - and can show how it made them faster, sharper, and more impactful. This is a high-impact, lead-leaning individual contributor role where your models and automation directly reduce financial loss and protect the integrity of the rewards experience for millions of members.

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

Sr. Data Scientist, Fraud Intelligence