Sr. Data Scientist, Fraud Intelligence

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.

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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 champion challenger 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…