Fraud and Lead Quality Analyst

Overview

Join to apply for the Fraud and Lead Quality Analyst role at Lending Tree
.

The Fraud and Lead Quality Analyst works under the direction of the Security Program Manager in a cross-functional capacity to build and maintain an enterprise-wide fraud detection and management program, and to ensure overall quality of leads passed to partners. The goal is high lead quality with low false positive/negative rates. The role involves data-driven analysis and operational management of fraud and lead quality programs, evaluating and upgrading fraud detection platforms, analyzing suspected organized fraud activity, monitoring security incidents, tailoring detection models to reduce false positives, improving non-fraud lead quality, and collaborating with business development and sales teams to tailor the program to each business vertical.

A feedback process with partners and marketing teams for continuous lead quality improvements is also required.

The position emphasizes data-driven management across data repositories (e.g., Snowflake, Sumo Logic) and presenting findings in business intelligence formats (Power

BI, Tableau). The candidate will partner with multiple business units to build an effective fraud management and lead quality assurance program tailored to Lending Tree’s unique risks and requirements.

• Provides ongoing data-driven analytics on fraudulent activity to improve the efficacy and accuracy of the fraud detection and management program.
• Provides ongoing data-driven analytics on overall lead quality to improve the value of the core business and support productive long-term partner relationships.
• Uses analyses to make data-driven improvements to both fraud and quality assurance programs.
• Works with vendors to evaluate and improve the value proposition of purchased fraud and quality control products and services.
• Uses API-based connectors to collect and transfer data from multiple sources to the Snowflake data warehouse.
• Writes custom queries in Snowflake and performs data manipulation to create live dashboards for real-time monitoring of fraudulent activity and other security data.
• Employs machine learning techniques to continually improve the accuracy and effectiveness of fraud and quality assurance programs.
• Collaborates cross-functionally to tailor fraud management and quality assurance programs to the risks of different business areas.
• Monitors the fraud detection program for suspected organized fraud incidents and coordinates with the Customer Contact Center to respond promptly.
• Works with partner financial institutions to investigate and remediate concerns about fraud or lead quality in a timely manner.
• Maintains compliance with regulatory requirements regarding fraud management and reporting across the company.
• Performs other information security related data analysis and presentation as required.

• At least two years of professional experience in fraud management or lead quality assurance, preferably in Fin Tech.
• Strong data analytics and data engineering skills, including experience with Snowflake, Sumologic, and BI tools like Tableau.
• Experience with fraud detection and management in Fin Tech, including knowledge of common fraud techniques.
• Experience with information security tooling such as SIEM/SOAR and Cloud security platforms (Cloudflare preferred).

• Experience with financial fraud management techniques including metadata analysis, identity matching, and automated activity detection.
• Experience with quality assurance techniques for contact information quality, OTP verification, and lead quality segmentation.
• Strong skills with Snowflake data warehouse and database analysis (SQL, DML, DDL, CTE).
• Proficiency with Power
  
  BI and Tableau for live-view dashboards.
• Knowledge of fraud attack vectors such as phishing, identity fraud, account takeovers, payment fraud, and platform impersonation.
• Knowledge of fraud detection platforms is a plus.
• Knowledge of machine learning models for real-time analysis and detection improvement is a plus.
• Knowledge of web infrastructure, APIs, and security concepts; familiarity with SIEM/SOAR and cloud security practices is…