Associate Fraud Analyst

Persona

About The Position

As an Associate Fraud Analyst, you will bridge high-quality fraud operations work and deeper analytical investigation. This role builds on strong labeling and fraud detection fundamentals and expands into structured fraud analysis, trend identification, and cross-functional collaboration. You will analyze fraud patterns, conduct structured audits, support customer-facing insights, and help translate operational learnings into actionable recommendations. You’ll work closely with Senior Labelers, Fraud Product Analysts, Product, Engineering, and Customer-facing teams to strengthen fraud detection strategies and improve outcomes for Persona customers. This role is ideal for someone who has strong fraud vector knowledge, enjoys digging into patterns and edge cases, and wants to grow into a more strategic, data-driven fraud role.

Requirements

Strong foundation in fraud detection, identity verification, or data labeling
Analytical mindset with the ability to identify patterns in ambiguous data.
Experience working with Excel or Google Sheets; basic SQL knowledge or willingness to learn.
Strong attention to detail and structured problem-solving skills.
Ability to clearly summarize findings in written format.
Comfort working cross-functionally in a fast-paced, evolving environment.
Curiosity about fraud tactics and emerging attack patterns.
Ownership mentality and desire to grow into a more strategic fraud role.

Nice To Haves

Experience supporting fraud audits or investigations.
Exposure to customer-facing work or summarizing insights for non-technical audiences.
Experience contributing to reporting frameworks or internal metrics tracking.

Responsibilities

Conduct structured fraud investigations across customer datasets.
Identify fraud patterns, trends, and emerging attack vectors.
Analyze edge cases and ambiguous signals to improve detection logic.
Support proactive and reactive fraud audits.
Use Excel or Google Sheets (and optionally SQL) to analyze fraud trends and quantify impact.
Track fraud metrics and surface insights that inform mitigation strategies.
Assist in preparing summaries of findings and recommended actions.
Contribute to dashboards or recurring reporting workflows.
Leverage deep labeling experience to provide context on data quality and model performance.
Partner with Senior Labelers to identify recurring annotation issues or instruction gaps.
Escalate systemic fraud trends and vulnerabilities to Fraud Product Analysts and Product teams.
Help refine fraud detection playbooks and internal documentation.
Support Fraud Product Analysts in customer investigations and deliverables.
Provide fraud insights that inform Product and Engineering decisions.
Participate in internal reviews of customer workflows, templates, and decisioning logic.