InfoStride
Contract Duration: 6–9 Months
About the Role The client is seeking a Fraud Specialist to join their Risk and Fraud team on a contract basis. In this critical role, you will help safeguard the company and its customers by analyzing fraud trends, refining detection systems, and mitigating risk—while minimizing false positives. The ideal candidate is both analytically strong and strategic, with hands‑on experience in fraud prevention within SaaS, fintech, or e‑commerce environments.
Key Responsibilities Track and report key fraud metrics (false positive rate, fraud‑to‑sales ratio, recall, etc.).
Analyze trends to identify vulnerabilities and drive strategic changes.
Manual Reviews & Case Management Validate flagged transactions and trial users to reduce false declines.
Reinstate legitimate customers and support a smooth user experience.
Rule and Model Optimization Design, test, and refine fraud detection rules and machine learning models.
Balance fraud prevention with business enablement.
Lead investigations for fraud alerts and chargebacks.
Document findings and apply process improvements to prevent recurrence.
Cross‑functional Collaboration Work closely with Product, Engineering, Legal, Finance, and Support teams.
Integrate fraud controls into billing, authentication, and compliance flows.
Subject Matter Expertise Act as the go‑to expert on fraud‑related issues across the organization.
Required Qualifications Bachelor's degree in business, Economics, Data Science, or related field.
5+ years of experience in fraud prevention, trust & safety, or risk management, ideally in SaaS, e‑commerce, or fintech.
Strong analytical background with hands‑on SQL skills.
Experience with fraud detection platforms, rule engines, and case‑management tools.
Proficiency in data tools such as Snowflake and Tableau.
Solid understanding of common fraud types (payment fraud, friendly fraud, SaaS‑related schemes).
Strong communication skills with ability to interface across technical and business teams.
Preferred Qualifications Familiarity with machine learning models in fraud detection.
Understanding of payment ecosystems, authentication protocols, and card networks.
Knowledge of relevant regulatory and compliance frameworks.
Seniority level Director
Employment type Contract
Job function Finance and General Business
Industries IT Services and IT Consulting, Financial Services, and Banking
Location San Francisco, CA
#J-18808-Ljbffr
About the Role The client is seeking a Fraud Specialist to join their Risk and Fraud team on a contract basis. In this critical role, you will help safeguard the company and its customers by analyzing fraud trends, refining detection systems, and mitigating risk—while minimizing false positives. The ideal candidate is both analytically strong and strategic, with hands‑on experience in fraud prevention within SaaS, fintech, or e‑commerce environments.
Key Responsibilities Track and report key fraud metrics (false positive rate, fraud‑to‑sales ratio, recall, etc.).
Analyze trends to identify vulnerabilities and drive strategic changes.
Manual Reviews & Case Management Validate flagged transactions and trial users to reduce false declines.
Reinstate legitimate customers and support a smooth user experience.
Rule and Model Optimization Design, test, and refine fraud detection rules and machine learning models.
Balance fraud prevention with business enablement.
Lead investigations for fraud alerts and chargebacks.
Document findings and apply process improvements to prevent recurrence.
Cross‑functional Collaboration Work closely with Product, Engineering, Legal, Finance, and Support teams.
Integrate fraud controls into billing, authentication, and compliance flows.
Subject Matter Expertise Act as the go‑to expert on fraud‑related issues across the organization.
Required Qualifications Bachelor's degree in business, Economics, Data Science, or related field.
5+ years of experience in fraud prevention, trust & safety, or risk management, ideally in SaaS, e‑commerce, or fintech.
Strong analytical background with hands‑on SQL skills.
Experience with fraud detection platforms, rule engines, and case‑management tools.
Proficiency in data tools such as Snowflake and Tableau.
Solid understanding of common fraud types (payment fraud, friendly fraud, SaaS‑related schemes).
Strong communication skills with ability to interface across technical and business teams.
Preferred Qualifications Familiarity with machine learning models in fraud detection.
Understanding of payment ecosystems, authentication protocols, and card networks.
Knowledge of relevant regulatory and compliance frameworks.
Seniority level Director
Employment type Contract
Job function Finance and General Business
Industries IT Services and IT Consulting, Financial Services, and Banking
Location San Francisco, CA
#J-18808-Ljbffr