# Fraud Patterns Analysts

**Company:** [Stripe](https://hotfix.jobs/companies/stripe)
**Location:** Remote
**Role:** Data Analytics
**Experience:** 5+ years
**Skills:** SQL, Python, Tableau, Splunk, Data Visualization, Fraud Detection, Root Cause Analysis, Clustering, Classification, Link Analysis
**Posted:** 2026-05-26

> Conduct advanced SQL-based data analysis and build fraud rulesets to detect and mitigate complex transaction fraud across payments and e-commerce. Collaborate with product, data science, and operations teams to implement risk controls and reduce fraud losses.

## Job Description

## Responsibilities
- Build and maintain fraud rulesets to prevent transaction level fraud losses, including ongoing monitoring and measurements of precision and recall
- Conduct advanced data analysis of structured and unstructured data sets to proactively identify emerging fraud attacks impacting Stripe and its users
- Collaborate closely with product, risk, and operations teams to proactively identify and mitigate fraud exposure
- Investigate, conduct root cause analysis, and deploy remediations to prevent future complex and distributed fraud attacks
- Investigate and take action against anomalous clusters of transactions based on account activity, processing volume, or other risk indicators while minimizing negative impacts to Stripe users
- Respond to incidents involving complex fraud schemes to quickly mitigate exposure to Stripe, its users, and financial partners
- Utilize analytics to identify & implement initiatives to automate manual processes and workload across the organization
- Create visualizations, dashboards, and queries to drive visibility and oversight into impact, performance, loss risks, and user experience
- Utilize Stripe tools & systems to enable systematic actioning of fraudulent merchants, maintaining an extremely high level of accuracy to prevent negative user experience

## Requirements
- Minimum of five years of experience conducting advanced data analysis & managing transaction fraud rulesets
- Advanced level proficiency in SQL
- Experience working closely with modeling, data science, and intelligence stakeholders to implement automatic & scaled controls & processes
- Experience creating data visualizations and dashboards & presenting findings to technical and non-technical audiences, including senior leadership
- The ability to drive execution on projects working in a heavily cross-functional environment
- Creativity, a team-focused mentality, and effective problem solving skills
- The ability and desire to question the status quo
- The ability to approach challenges from a user perspective while being pragmatic & solutions oriented

## Nice-to-Haves
- Fraud experience in payments, e-commerce, fintechs, or cryptocurrency mitigating digital/card-not-present fraud
- Experience investigating and mitigating card testing and account takeover attacks
- Proficiency in Splunk, Python, Tableau, or other data visualization tools
- Undergraduate or advanced degree in analytics, data science, or statistics
- Experience with clustering, classification, & link analysis
- Experience working in fast-paced and rapidly changing environments
- Experience designing and implementing product level fraud and risk controls

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