Staff Fraud Analyst

What you'll do

• Architect and scale robust table structures and analytics using expert-level SQL and Python for global risk detection.
• Design sophisticated fraud decisioning strategies by synthesizing login, entity, and tokenization signals to neutralize complex threats.
• Translate intricate technical risks into high-level business logic to align stakeholders on security versus user friction.
• Optimize detection precision through rigorous statistical analysis and False Positive Rate modeling to protect the customer experience.
• Execute end-to-end risk-decisioning procedures for debit card transactions and authentication frameworks like MFA and 3DS.
• Develop data-driven fraud decisioning to mitigate risks associated with Account Takeover (ATO) and high-risk transactions.

What we're looking for

• BA/BS in Statistics, Information Systems, Mathematics, Data Science, or related fields, or equivalent work experience.
• 5+ years of work experience in Fraud Analytics.
• Experience managing risk-decisioning strategies and mitigating losses in debit card fraud transaction flows including ATO, 3DS, CNP, and Tokenization.
• Knowledge of sophisticated authentication frameworks including MFA/IDV.
• Expert-level SQL and Python skills to build automated data architectures and statistical models.
• Mastery of the trade-off between fraud mitigation and user experience metrics.
• Ability to lead cross-functional initiatives and translate technical risks into business logic for stakeholders.