Fraud Analyst

VIDA is a digital identity company on a mission to make trust simple, secure, and accessible in a digital-first world. We work with enterprises and institutions to prevent fraud, enable compliant growth, and protect users through cutting-edge identity verification and risk intelligence solutions.

As fraud continues to evolve in scale and sophistication—especially with AI-driven attack vectors—VIDA is building a world-class fraud and risk capability grounded in data, science, and real-world impact.

We are looking for a Fraud Analyst to join our Data Science organization and work closely with our Chief Data Science Officer. This role sits at the intersection of fraud intelligence, data analysis, and product impact.

You will analyze fraud patterns across identity verification, onboarding, and transaction flows; generate actionable insights; and help inform both model development and business decisions. This is a hands-on role with high visibility and the opportunity to shape how VIDA detects, understands, and mitigates fraud at scale.

Fraud Analysis & Intelligence

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  Analyze fraud trends, patterns, and anomalies across VIDA’s products and client use cases.
  
  

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  Investigate fraud cases and networks, including emerging and AI-enabled fraud typologies.
  
  

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  Own the end-to-end fraud rules lifecycle—from data analysis and hypothesis formation to rule design, testing/validation, deployment to production, and ongoing monitoring/optimization to prevent real-world fraud. 
  
  

Data & Model Collaboration

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  Work closely with data scientists and engineers to support fraud detection models, rules, and risk strategies.
  
  

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  Help define fraud labels, evaluation metrics, and feedback loops to improve model performance.
  
  

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  Validate model outputs and translate results into business-relevant insights.
  
  

Reporting & Communication

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  Build dashboards, reports, and analyses for internal stakeholders, including Product, Risk, and Leadership.
  
  

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  Present findings and recommendations to the CDSO and cross-functional teams.
  
  

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  Contribute to thought leadership, whitepapers, or external-facing insights on fraud trends (as appropriate).
  
  

Process & Strategy Support

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  Help improve fraud monitoring processes, investigation workflows, and documentation.
  
  

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  Support experimentation and A/B testing of fraud controls or detection strategies.
  
  

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  Stay current on global fraud trends, regulatory developments, and adversarial tactics.
  
  

• 2–5+ years of experience in fraud analysis, risk analytics, data analysis, or a related field.
  
  

• Strong analytical skills with the ability to interpret complex datasets and identify meaningful patterns.
  
  

• Proficiency in SQL; experience with Python is a strong plus.
  
  

• Experience working with fraud, risk, identity, payments, or trust & safety data.
  
  

• Ability to clearly communicate insights to both technical and non-technical audiences.
  
  

• Experience in digital identity, fintech, payments, or cybersecurity environments.
  
  

• Familiarity with machine learning concepts and how fraud models are built and evaluated.
  
  

• Experience working with large-scale or real-time data systems.
  
  

• Exposure to global fraud patterns and cross-market risk dynamics.
  
  

• Curious, skeptical, and detail-oriented—someone who enjoys uncovering “what’s really going on” in the data.
  
  

• Comfortable working in ambiguity and evolving problem spaces.
  
  

• Strong sense of ownership and accountability.
  
  

• Able to balance precision with pragmatism in a fast-moving environment.