Own the metrics, dashboards, and reports that inform business strategy and decision-making.
Design and implement real-time monitoring systems for fraud signals and alerting thresholds.
Design, simulate, and implement real-time risk controls using real-time and offline predictive ML models.
Balance risk controls with customer experience by focusing on loss savings, reduced user friction and margin improvement.
Partner with go-to-market teams to demonstrate the technical and business value of risk controls to customers.
Effectively summarize complex analytical results to leadership and non-technical stakeholders.
Assist partners when they have fraud concerns with their traffic.

Requirements

Advanced proficiency in SQL and Python.
3+ years hands-on experience working on automated fraud risk strategies and experimentation (A/B tests) including implementation of real-time and offline predictive ML models.
Skilled in designing, building, and maintaining dashboards and fraud risk metrics.
The ability to manage ambiguous problems and find solutions.
High autonomy including the ability to prioritize your workload effectively.
Relevant quantitative bachelor’s (or higher) degree (Statistics, Mathematics, Engineering, Computer Science, etc.).
Bonus attributes: Experience at a high-growth fintech company or financial services company; exposure to customer-facing or GTM-facing analytics or fraud issue triaging; background in identity risk, AML, payments fraud, or compliance analytics.

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

SQLPythonreal-time monitoring systemspredictive ML modelsA/B testingdashboard designfraud risk metricsrisk controlsdata analysisquantitative analysis

problem-solvingautonomyprioritizationcommunicationanalytical thinkingcollaborationpresentation skillscustomer focusadaptabilitystakeholder engagement

bachelor's degreemaster's degree