What are the responsibilities and job description for the Fraud Analyst position at InfoStride?
Few Details about the role
Client is seeking a detail-oriented and proactive Fraud Specialist to join our team as a
contractor. In this critical role, you will partner with the Fraud team and help our organization
protect both our business and our customers. You will blend deep analytical skills with strategic thinking to monitor, investigate, and mitigate fraud risks and keep false positives to a minimum.
Your work will directly impact our revenue, customer trust, and user experience by helping
ensure that our fraud prevention systems are both effective and efficient.
Responsibilities
Monitor and analyze fraud KPIs. Define, track, and report on fraud metrics—including
block vs. false positive rates, incoming fraud pressure, recall, fraud‑to‑sales ratio, and
good user approval rate. Use these indicators to identify trends and gaps, fine‑tune
rules, and measure false‑positive impacts.
Validate false positives. Perform manual reviews for flagged trials and purchases,
verifying legitimate customers are not incorrectly declined. Work with internal
stakeholders to reinstate valid users and gather feedback on user experience.
Design and refine controls. Test and adjust fraud detection rules, scoring models and
machine‑learning algorithms to mitigate risk without overblocking. Ensure models
maintain high precision and recall while keeping false positives low.
Lead incident response. Coordinate investigations of fraud alerts and chargebacks,
ensuring timely resolution and communication with affected stakeholders. Document root
causes and adjust processes to prevent future incidents.
Cross‑functional collaboration. Partner closely with Product, Marketing, Engineering,
Data Science, Legal, Finance and Customer Support teams to integrate fraud controls
into product flows, billing systems and compliance processes.
Act as the primary point of contact and subject matter expert for all fraud-related
matters within the organization.
What You Bring
Basic Qualifications
Bachelor’s degree in Business, Economics, Data Science, or a related field
5 years of experience in fraud prevention, trust & safety, or risk management—ideally
within a SaaS, e‑commerce, or fintech environment.
Demonstrated ability to analyze large datasets, identify patterns, and drive data‑driven
decisions.
Proficiency in SQL and experience with data tools such as Snowflake and Tableau.
Deep understanding of fraud typologies (payment fraud, SaaS fraud, friendly fraud) and
experience with fraud detection platforms, rule engines and case‑management tools.
Excellent communication and interpersonal skills; comfortable collaborating with diverse
teams and presenting insights to executives.
Preferred Qualifications
Familiarity with applying machine‑learning models in fraud detection contexts.
Knowledge of payment processing ecosystems, card networks and authentication
methods.
Understanding of regulatory and compliance frameworks
