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Lead Fraud Data Analyst

August 31

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Logo of Varo Bank

Varo Bank

We're on a mission to bring financial inclusion and opportunity to all.

Mobile Banking • User Interface • Financial Services • Risk Management • Design Research

501 - 1000

Description

•Develop new data driven rules that optimize decisioning performance between member experience and fraud prevention •Work with external fraud prevention vendors to optimize their performance and assist in maintaining, design and implementation of existing and new fraud detection tools •Aggregate and analyze internal and external risk datasets to understand performance of fraud decisioning and granular performance of multiple decision methods •Find insights from risk data sets to improve fraud strategies and rules •Participate in regular review of activities involving different fraud topologies •Able to lead fraud/risk investigations for both simple and complex cases to successful conclusions and mark false positives and false negative cases •Complete investigation of customers and transactions flagged by the Bank's automated monitoring system(s), manual reports, and/or referrals •Define, implement, and manage rule rationalization and governance process •Manage responsibilities for 3-4 junior analysts, help with prioritization, and review work

Requirements

•7+ years of fraud or risk experience focused on the risk strategy and risk analytics •Experience working at a FinTech or start-up is a plus •3+ years of experience in SQL queries, Tableau (and other BI tools), and day-to-day use of R/Python is a plus •Strong knowledge of financial products, including ACH, RDC, debit cards, credit cards, lending products, and deposit accounts •Knowledge of fraud management systems such as Falcon, RSM, JackHenry, Iovation, Threat metrics, Verafin, etc •Deep understanding of the financial fraud space •Experience creating and optimizing fraud prevention rules and strategies •Knowledge of a scripting programming language such as Python •Strong BI and analytics skills and knowledge of tools such as SQL/Athena Rule rationalization and governance •Coaching and mentoring other analysts •Cross-functional stakeholder management, working with engineers, product, operations, and data science

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