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Description:
The Senior Fraud Data Analyst is responsible for designing unique analytic approaches to detect, assess, and mitigate fraud risk.
You will help analyze the effectiveness of day-to-day fraud policies and rules in fraud systems.
The role involves analyzing large amounts of account and transaction data to develop and improve processes and models while managing the customer experience.
This position requires fast-paced, time-sensitive turnaround and offers a rewarding opportunity to help fight deposit and lending fraud daily.
Responsibilities include developing new data-driven rules that optimize decision-making performance between member experience and fraud prevention.
You will work with external fraud prevention vendors to optimize their performance and assist in maintaining, designing, and implementing existing and new fraud detection tools.
The role involves aggregating and analyzing internal and external risk datasets to understand the performance of fraud decision-making and the granular performance of multiple decision methods.
You will find insights from risk data sets to improve fraud strategies and rules.
Participation in regular reviews of activities involving different fraud topologies is expected.
You will lead fraud/risk investigations for both simple and complex cases to successful conclusions and mark false positives and false negative cases.
Completing investigations of customers and transactions flagged by the Bank's automated monitoring systems, manual reports, and/or referrals is part of the job.
You will define, implement, and manage the rule rationalization and governance process.
Requirements:
A minimum of 5 years of fraud or risk experience focused on risk strategy and risk analytics is required.
Experience working at a FinTech or start-up is a plus.
At least 3 years of experience in SQL queries, Tableau (and other BI tools), and day-to-day use of R/Python is preferred.
Strong knowledge of financial products, including ACH, RDC, debit cards, credit cards, lending products, and deposit accounts is necessary.
Knowledge of fraud management systems such as Falcon, RSM, JackHenry, Iovation, Threat metrics, Verafin, etc., is required.
A deep understanding of the financial fraud space is essential.
Experience creating and optimizing fraud prevention rules and strategies is necessary.
Knowledge of a scripting programming language such as Python is required.
Strong BI and analytics skills and knowledge of tools such as SQL/Athena for rule rationalization and governance are needed.
The ability to coach and mentor other analysts is important.
Cross-functional stakeholder management experience, working with engineers, product, operations, and data science, is required.
Benefits:
The salary range for this role is between $100,000 and $150,000 per year.
Cash compensation is benchmarked against similar-stage growth companies based on function, level, and geographic location.
Final offer amounts are determined by multiple factors, including candidate experience and expertise, and may vary from the identified range.