Fraud Data Scientist (P4)

The Fraud Data Scientist (P4) is responsible for leveraging data analytics, statistical modeling, and fraud detection techniques to identify suspicious activity, uncover fraud trends, and support fraud loss prevention efforts. This role partners with Fraud Strategy, Fraud Operations, Product, Technology, and Operations teams - including Customer Experience & Service (CES), BSA/AML Operations, and Disputes - to develop actionable insights, optimize customer experience outcomes, and improve fraud detection capabilities. The position applies established analytical methodologies to solve complex business problems and contributes to the design, testing, and optimization of fraud rules, models, and monitoring strategies.

You might be the right match for this role if:

• You enjoy using data to solve business problems and identify opportunities to improve fraud prevention and detection efforts.
• You are comfortable working with large datasets and applying analytical techniques to generate actionable business insights.
• You can independently manage work assignments while collaborating effectively with cross-functional partners, including Operations, CES, and BSA/AML teams.
• You possess strong technical and analytical capabilities and can clearly communicate findings to both technical and non-technical audiences.
• You have a continuous improvement mindset and seek opportunities to enhance fraud detection capabilities, reporting, and operational effectiveness - including reducing customer-impacting friction., * Analyzing data to identify fraud patterns, suspicious activity, and emerging fraud trends, and communicating findings to business stakeholders.
• Supporting the development, testing, implementation, and ongoing optimization of fraud rules and detection strategies designed to mitigate fraud risk and losses.
• Performing exploratory data analysis using structured and unstructured data sources to support fraud investigations and detection initiatives.
• Developing analytical models, scorecards, and reporting solutions that improve visibility into fraud performance and operational effectiveness.
• Writing and maintaining SQL, Python, SAS, or similar code to extract, transform, and analyze large datasets from multiple sources.
• Collaborating closely with Fraud Strategy, Product, Engineering, and Operations teams - including Customer Experience & Service (CES), BSA/AML Operations, and Dispute Operations - to align fraud analytics initiatives with operational workflows and deliver improvements to the end-to-end customer experience.
• Partnering with CES and Operations to translate customer friction signals, dispute trends, and operational case data into actionable rule tuning and strategy enhancements that reduce unnecessary declines and streamline customer resolution pathways.
• Coordinating with BSA/AML Operations to ensure fraud signals and SAR-adjacent trends are surfaced appropriately, supporting compliant and consistent cross-functional response to emerging threats.
• Creating dashboards, visualizations, and reports that communicate key fraud trends, performance metrics, and insights to business leaders.
• Participating in model monitoring, validation, and performance analysis to ensure fraud detection strategies remain effective over time.
• Supporting projects and analytical initiatives under the guidance of senior team members while demonstrating increasing independence in problem solving and solution development.

• Bachelor’s degree in Statistics, Mathematics, Computer Science, Engineering, Data Science, or a related field.
• 5-8 years of experience in data science, analytics, fraud analytics, risk analytics, or a related field.
• Experience working with analytical tools and programming languages such as SQL, Python, SAS, or similar technologies.
• Experience performing statistical analysis, data mining, segmentation, trend analysis, and model evaluation.
• Ability to work with large and complex datasets and derive actionable business insights.
• Strong communication and presentation skills.

Preferred Qualifications

• Experience in fraud prevention, fraud strategy, fraud operations, payments, fintech, banking, or financial services.
• Experience supporting fraud rule platforms, fraud models, or fraud strategy initiatives.
• Experience with Falcon, PRM, VRM, SecurLOCK, Mastercard Connect, SageMaker, SAS, or similar fraud and analytics platforms.
• Experience with data visualization tools such as Tableau, Power BI, or similar business intelligence platforms.
• Familiarity with dispute operations, BSA/AML compliance workflows, or customer operations environments.

Ability to work in the U.S. without sponsorship

We’re looking for talented professionals to join us in bringing smart money management and payment solutions to everyone’s fingertips.

This position is classified as structured hybrid, with an expectation of three (3) days per week working in the office and flexibility to work remotely on the remaining days. On-site expectations may evolve over time to support business needs, with clear communication provided in advance.