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Fraud and Risk Analyst

Scale AI

HybridHybrid

Original Job Summary

Overview

The Fraud and Risk Analyst at Scale AI is responsible for managing and resolving complex, high-impact cases involving fraud, scams, privacy, compliance, and emerging risk trends. This role requires deep risk assessments, SQL-driven data analysis, and collaboration with Product, Engineering, and Policy teams to enhance global trust and safety operations.

Responsibilities

  • Manage and resolve complex fraud, scam, and compliance cases.
  • Conduct deep risk assessments and investigations using internal tools and third-party data.
  • Utilize SQL and advanced data analysis to detect anomalies.
  • Collaborate across teams to design operational workflows and automation systems.
  • Translate case insights into actionable feedback and develop playbooks, SOPs, and macros.
  • Monitor performance via case quality reviews, SLA tracking, and user satisfaction metrics.
  • Lead or contribute to global safety initiatives and provide vendor training.

Requirements

  • 4+ years in Trust & Safety, Fraud Prevention, Scam or Risk Operations, Compliance, or related areas.
  • Strong proficiency in SQL and data analysis.
  • Deep understanding of global privacy, regulatory, and risk management frameworks.
  • Excellent communication, problem-solving skills and high empathy.
  • Ability to thrive in fast-paced, high-autonomy environments while managing multiple priorities.

Key Skills/Competency

  • Risk Management
  • Fraud Prevention
  • SQL
  • Data Analysis
  • Compliance
  • Investigations
  • Privacy
  • Operational Workflows
  • Playbooks
  • Global Safety

How to Get Hired at Scale AI

🎯 Tips for Getting Hired

  • Customize your resume: Tailor experiences to risk analysis roles.
  • Research Scale AI: Understand their products, values, and culture.
  • Highlight SQL skills: Demonstrate strong data query proficiency.
  • Prepare for case studies: Practice solving risk assessment scenarios.

📝 Interview Preparation Advice

Technical Preparation

Review SQL query techniques.
Practice detecting data anomalies.
Refresh data analysis fundamentals.
Familiarize with risk assessment tools.

Behavioral Questions

Describe a past investigative challenge.
Explain teamwork under pressure.
Detail prioritization during multiple projects.
Share an example of empathetic problem solving.