Lead Fraud Analyst

Overview

Blend is seeking a Fraud Analytics Lead Analyst to support fraud strategy and analytics across our financial services this role you will leverage data to identify fraud trends uncover emerging risks and develop strategies that help prevent fraud across the payments lifecycle.

You will work in a highly collaborative data-driven environment partnering with fraud risk analytics and technology teams to improve fraud detection reduce losses and strengthen controls against evolving fraud threats.

What Youll Be Doing

• Analyze large datasets to identify fraud trends patterns and emerging risks across payment and card portfolios.
• Develop and support fraud risk strategies across the full fraud lifecycle including application fraud synthetic identity fraud and account takeover.
• Translate complex data into actionable insights that drive fraud prevention strategies and business decisions.
• Partner with Fraud Policy Operations Risk and Technology teams to implement optimize and enhance fraud decision strategies.
• Support the testing implementation monitoring and continuous improvement of fraud decision systems.
• Create reports dashboards and analytical insights to measure strategy performance and identify optimization opportunities.
• Assist with fraud model monitoring validation and performance evaluation within production environments.
• Document analyses findings and recommendations and present insights to business partners and senior leadership.

Qualifications :

Required Experience

• Hands-on experience in fraud analytics within the payments industry including credit cards banking fintech or other financial services.
• Strong analytical background working with large complex datasets in Big Data environments.
• Proficiency with data analysis tools such as SQL Python SAS Hive or similar technologies.
• Demonstrated ability to identify fraud patterns trends anomalies and actionable insights from complex data.
• Experience supporting business decisions through data analysis reporting and strategic recommendations.

Preferred Qualifications

• Experience working with fraud models including model monitoring validation or performance evaluation.
• Familiarity with fraud decision engines rules-based strategies or fraud strategy implementation.
• Exposure to risk management regulatory or financial services environments.
• Excellent communication and presentation skills with the ability to explain complex analytical findings to both technical and non-technical stakeholders.

Education

• Bachelors degree in Mathematics Statistics Economics Computer Science Data Analytics Finance or another quantitative field.

What This Role Requires

This is not a general Data Analyst position. Successful candidates will have direct hands-on experience in fraud analytics within the payments industry and be comfortable working in large-scale data-intensive environments. You should have a proven ability to leverage data to identify fraud risks develop actionable insights and support strategies that reduce fraud losses while improving the customer experience.

Remote Work :

No

Employment Type :

Contract