Job Description

This senior role of fraud analytics is responsible for designing unique analytic approaches to detect, assess, and mitigate fraud risk. You will help analyze the effectiveness of our day-to-day fraud policy and rules in our fraud systems. You will analyze large amounts of account and transaction data to build actionable insights to derive the methods to identify fraud risk, reduce friction and enhance experience on money movement. This role requires critical thinking and analytical savviness to work in a fast-paced environment but can be a rewarding opportunity to help bring a secured banking experience.

• Develop new data driven rules that optimize decisioning performance between member experience and fraud prevention.
• Develop data insights and rules to help understand customers’ banking behavior and preferences to drive first party fraud controls and strategy for payment and lending.
• Develop personalized segmentations and micro-segmentation to identify customers based on their fraud risk, banking behaviorals, and value.
• 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

• 10+ years of fraud or risk experience focused on the risk strategy and risk analytics in financial services, insurance, and healthcare industries. FinTech or start-up experience is a plus. First party fraud risk management experience is a plus.
• 8+ years of data analytics experience with hands-on SQL and python coding is a plus 
• 3+ years of experience in Tableau (and other BI tools).
• 3+ years of experience analyzing data with statistical approaches with python (e.g. in Jupyter notebook): for example, clustering analysis, decision trees, linear regression, logistic regression, correlation analysis.
• 1+ years of hands-on use of AWS (e.g. S3, EC2, EMR, Athena, SageMaker and more) is a plus.
• Strong knowledge of financial products, including fraud management in lending products, ACH, RDC, P2P, and deposit accounts. 
• Knowledge of fraud management systems such as Sentilink, iOvation, Lexisnexis, etc
• Deep understanding of the financial fraud space
• Experience creating and optimizing fraud prevention rules and strategies
• Coaching and mentoring other analysts
• Cross-functional stakeholder management, working with engineers, product, operations, and data science

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