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Tier-1 employer, mid-level experience band, and metro location increase applicant density.
Role requires specialized fraud prevention experience and fintech domain knowledge, limiting cross-industry transferability.
Explicit 4+ years, required fraud domain experience, SQL/Python and regulatory knowledge make filters stringent.
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Analyze and strategize on fraud risk across the platform focusing on account takeover (ATO), suspicious activities, and financial product access controls.
Develop and optimize fraud detection rules, algorithms, and risk controls using SQL and Python, working closely with cross-functional teams including data science, security, and compliance.
Conduct data-driven investigations and cost-benefit analyses to improve fraud prevention while balancing user experience and operational efficiency.
4+ years in fraud prevention, detection, risk analytics, or closely related analytical roles, preferably in fintech.
Bachelor's degree in Mathematics, Statistics, Computer Science, Economics, or related field; Master's degree preferred.
Proficiency in SQL and Python for complex fraud data analysis and strategy support.
Work primarily in-office at least three days a week, within commuting distance to a Rippling office according to current policy.
Experienced in analyzing account takeover risks and suspicious activity patterns with hands-on expertise in fraud prevention methodologies.
Skilled at developing and refining detection logic and working collaboratively with security, product, and compliance teams.
Proficient at translating complex data insights into actionable recommendations for diverse stakeholders, and comfortable navigating ambiguous problem spaces.