Staff Risk Analyst, Fraud Program

Who we are:

Shape a brighter financial future with us. Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation fintech company using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world.

The Role

The Fraud Prevention team is looking for an experienced Staff Fraud Risk Analyst with a background in Model Risk Management or Model Governance. The Staff Fraud Risk Analyst will assist the Fraud Center of Excellence (CoE)in driving critical fraud related projects and will be responsible for proactively and collaboratively supporting the monitoring and oversight of the fraud ecosystem- including technology, model governance, and risk analytics reporting. This role will also have a critical responsibility for ensuring that the bank’s fraud risk models are robust, effective, and compliant with regulatory requirements. The incumbent will oversee the governance framework around the design, development, validation, and deployment of fraud models. 

The ideal candidate will have a strong data background, including proficiency in SQL, Python, Snowflake, and Tableau. You’ll need to be a self-motivated leader with the ability to drive cross-functional collaboration between all lines of business; and have a mission to iterate and develop a world-class fraud prevention platform. If you love working with data and have a passion for doing the right thing, we want to hear from you!

What you’ll do:

• Oversee the fraud model governance framework, ensuring that it meets regulatory standards and industry best practices
• Maintain comprehensive documentation for all fraud models, and report on model performance, changes, and validation results to senior management and regulatory bodies as required
• Document how the models are built, tested and validated, methodology, sampled and performance monitored
• Conduct periodic model validation on scores reviewing precision, recall, rank ordering of score performance, detection of PSI and other metrics as needed
• Ensure continuous monitoring of fraud models' performance to identify and address model drift or degradation
• Address any identified issues or gaps in the fraud model governance process and ensure timely resolution
• Work with the Fraud Ecosystem teams to monitor fraud patterns and identify potential risks and threats
• Assist in the development of fraud risk metrics, reporting, and monitoring
• Develop and maintain reports and dashboards in Tableau to provide insights and trends to management
• Collaborate with business units across the CoE to assess and refine fraud prevention measures to ensure effectiveness and highlight areas for improvement
• Assist in the development of analytic projects involving ongoing fraud prevention efforts between the Fraud Program Management team and other Strategic, Analytic, and Operational partners.

What you’ll need:

• 6+ years of data analysis experience preferably with focus on risk management and/or fraud prevention
• Mastery of SQL and a strong understanding of data relationships / relational databases, experience working with large datasets
• Advanced skill sets in other programming and data analysis tools such as Python, R, or SAS
• Experience working with Snowflake and Tableau
• A degree in a quantitative field of study (e.g., Statistics, Finance, Economics, Math, Sciences, Engineering)
• Exceptional writing and presentation abilities are highly desirable
• Deep knowledge of regulatory requirements pertaining to model risk management in the banking sector
• Excellent communication skills with the ability to articulate complex technical concepts to non-technical audiences
• Proactive with a strong sense of ownership and accountability, and the ability to independently execute

Nice to Have:

• Advanced degree in Data Science or Machine Learning
• Experience in implementing or overseeing AI/ML-based models for fraud detection
• Experience working in or working closely with model risk management