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The Disbursement Analyst ensures efficient money transfer processes at Felix, analyzing data to optimize disbursement metrics and resolve routing issues while boosting user experience for Latino immigrants.

The Data Analyst will enhance remittance operations by analyzing transaction data, improving disbursement processes, and designing performance metrics dashboards while ensuring user satisfaction and operational efficiency.

The Disbursement Analyst will optimize transaction processes by analyzing data, maintaining performance dashboards, driving defect reduction, and communicating insights to stakeholders, focusing on improving user experiences in remittances.

Architect and build a scalable frontend platform for CX operational tooling: design modular frontend architecture, secure data aggregation layers and API proxies, improve developer experience (DX), optimize builds and CI/CD, collaborate with stakeholders to streamline workflows, and mentor engineers on frontend best practices, accessibility, and code quality.

Own the identity and account platform including onboarding, verification, authentication, data schemas, and cross-team identity experience. Drive product vision, roadmap, KPIs, and AI-driven identity innovations while aligning Engineering, Design, Fraud, and Compliance for secure, scalable identity solutions.

Lead the design and scaling of a unified fraud and risk platform. Define product roadmap, run data analysis and A/B tests, collaborate with engineers and data scientists to build real-time fraud detection, manage stakeholders, and balance customer experience with effective risk mitigation.

Lead the fraud data science function: define ML strategy, build and productionize fraud detection models, investigate fraud patterns, run experiments, collaborate with Product/Engineering/Risk, and deliver dashboards and monitoring to minimize fraud losses while preserving customer experience.

Own the identity and account platform covering onboarding, verification, authentication, account lifecycle, and security. Define identity flows, data schemas, KPIs, and roadmap. Lead cross-functional alignment with Engineering, Design, Fraud, and Compliance. Drive AI-enabled identity innovations and communicate strategy to stakeholders and executives.

Lead the fraud data science effort: define ML strategy, build and productionize real-time fraud detection models, investigate fraud patterns with unsupervised and graph techniques, run experiments, collaborate with product/engineering/risk, and maintain dashboards to monitor model performance and fraud KPIs.

Lead design and scaling of a unified fraud and risk platform. Define product strategy, own fraud metrics, run SQL-driven analysis and A/B tests, and partner with engineers and data teams to build real-time detection, identity verification, and transaction monitoring. Balance customer experience with risk mitigation and communicate impact to executives, legal, and partners.