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StripeStripeUnited States

Fraud Patterns Analysts

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.

Salary not listed
Remote5+ YOEData Analytics

About the role

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

Skills

SQLPythonTableauSplunkData VisualizationFraud DetectionRoot Cause AnalysisClusteringClassificationLink Analysis

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