Senior Fraud Risk Analyst –SME - Customer Success (Technical & Client-Facing)

New
MexicoFull-TimeSenior
Salary not disclosed
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Job Details

Languages
Fluent in English and Spanish (mandatory).
Experience
5+ years of experience in Fraud Risk, Financial Crime, Risk Consulting, or similar analytical and client-facing roles.
Required Skills
SQLData Analysis

Requirements

  • 5+ years of experience in Fraud Risk, Financial Crime, Risk Consulting, or similar analytical and client-facing roles.
  • Strong expertise in fraud typologies such as ATO, APP fraud, mule activity, and digital/payment fraud across banking or fintech environments.
  • Advanced SQL skills with experience analyzing large datasets to detect fraud patterns and high-risk signals.
  • Proven experience working with ML-based and rule-based fraud detection systems, including tuning and operationalizing fraud rules.
  • Strong ability to translate technical model behavior into business impact, including risk trade-offs, false positives, and loss prevention outcomes.
  • Experience leading client workshops, managing enterprise stakeholders, and supporting end-to-end implementation projects.
  • Strong communication skills with the ability to simplify complex analytical and technical concepts for diverse audiences.
  • Fluent in English and Spanish (mandatory).

Responsibilities

  • Act as a subject-matter expert in fraud and digital trust, leading strategic workshops and executive-level discussions with enterprise clients.
  • Translate fraud trends, analytics, and machine-learning outputs into clear business actions and risk decisions that improve detection and reduce losses.
  • Interpret complex datasets and model outputs using SQL and analytical tools to identify anomalies, fraud patterns, and operational risks.
  • Convert fraud insights into structured technical requirements for Product, Engineering, and Data Science teams to enhance platform capabilities.
  • Support fraud platform implementations by configuring detection rules, thresholds, scoring models, and operational workflows.
  • Collaborate cross-functionally to improve fraud strategies, contribute to product evolution, and ensure continuous alignment between clients and internal teams.
  • Manage senior client relationships, balancing advisory leadership with hands-on execution and operational optimization.
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