Staff Risk Analyst, Fraud Program Management

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Who we are:

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guiding us every step of the way. Join us to invest in yourself, your career, and the financial world.

The Role

The Fraud Program is seeking a Staff Risk Analyst to lead data governance initiatives, analytics, and reporting across
the Fraud Center of Excellence (CoE). This role will serve as a key partner in developing, maintaining, and enhancing
fraud KPIs, KRIs, dashboards, and enterprise risk reporting to enable data-driven decision making and effective fraud
risk oversight.

The Staff Risk Analyst will play a critical role in ensuring data integrity, consistency, and transparency across fraud
metrics, while delivering actionable insights into fraud performance, emerging risks, and operational effectiveness
across all products and fraud domains.

This role will partner closely with Fraud Strategy, Operations, Risk, Data, and Business Intelligence teams to build
scalable analytics solutions, standardize metric definitions, and improve enterprise-wide visibility into fraud risk.
The ideal candidate will bring a strong technical data background, experience in risk analytics, and a passion for
building scalable data and reporting frameworks within a fast-paced fintech environment. Additionally, the
candidate will also have strong 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. IIf you love working with
data and have a passion for doing the right thing, we want to hear from you!

What you’ll do:

Fraud Data Analytics, Insights, and Data Governance (Primary Focus)
● Analyze fraud data across products and channels to identify trends, anomalies, and emerging fraud risks.
● Develop data-driven insights and recommendations to support fraud strategy, operations, and risk
management decisions.
● Partner with cross-functional teams to translate business problems into analytical solutions that improve
fraud detection, prevention, and member experience.
● Establish and enforce data governance standards for fraud metrics- including data definitions, lineage, and
controls; and effectively leading a strategic data governance council cross-functionally.
● Identify and resolve data quality, consistency, and availability issues impacting fraud reporting and
analytics.
● Partner with Data Engineering and BI teams to ensure reliable, scalable, and well-documented data
sources.
KPI / KRI Framework & Performance Monitoring
● Support the design, development, and ongoing enhancement of Fraud KPIs, KRIs, and Risk Appetite

Statement (RAS) metrics across the Fraud CoE.

● Ensure consistent metric definitions, calculations, and reporting methodologies across business units.
● Monitor metric performance and provide insights into drivers of variance, trends, and risk signals.
Dashboarding & Reporting
● Assist in designing, building, and maintaining Tableau dashboards and automated reporting solutions to
provide real-time visibility into fraud performance.
● Deliver executive-level reporting and visualizations for fraud governance committees and leadership.
● Improve reporting efficiency through automation and scalable data pipelines (e.g., Snowflake), where
needed, in partnership with our risk analytics and data teams
Fraud Risk Management & Assessment Support
● Support Fraud Risk Self-Assessments (FRSA) and other risk evaluation activities through data analysis and
metric development.
● Assist in identifying key risk drivers and areas of elevated fraud exposure across products and processes.
● Provide analytical support for audit, regulatory, and risk management requests.
Cross-Functional Collaboration & Program Support
● Collaborate with Fraud Strategy, Operations, and Program teams to align data, metrics, and reporting with
business needs.
● Support broader Fraud Program initiatives and analytics projects as needed, including strategy
performance analysis and operational insights.

What you’ll need:

● 4+ years of experience in data analytics, fraud analytics, or risk analytics within financial services, fintech, or
banking.
● Strong experience working with large datasets and relational databases.
● Advanced proficiency in SQL and experience with Snowflake or similar data platforms.
● Experience building dashboards and data visualizations (Tableau preferred).
● Strong understanding of KPI/KRI frameworks, performance metrics, and risk monitoring concepts.
● Experience with data governance, data quality management, or metric standardization.
● Strong analytical and problem-solving skills with the ability to translate complex data into actionable
insights.
● Excellent communication skills, with the ability to present findings to both technical and non-technical
stakeholders.
● Ability to work cross-functionally and manage multiple priorities in a fast-paced environment.
● Proficient in other programming and data analysis tools such as Python, R, or SAS.

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 is a plus.