Fraud and Lead Quality Analyst

Overview

PLEASE NOTE:

This role requires in-office attendance in our Charlotte, NC office (hybrid schedule; Tuesday-Thursday in-office).

Under the direction of the Security Program Manager, the Fraud and Lead Quality Analyst works in a cross-functional capacity to build and maintain an efficient enterprise-wide fraud detection and management program, as well as ensuring overall quality of leads passed to partners, with the goal of ensuring high lead quality and low false positive/negative rates. The Analyst is responsible for providing data-driven analysis and operational management of our fraud and lead quality management program, including evaluating, maintaining, and upgrading various fraud detection platforms, performing analysis of suspected organized fraud activity, monitoring for fraud-related security incidents, tailoring our detection models to reduce false positives, improve non-fraud lead quality, and working with the business development and sales teams to produce a fraud program that is tailored to the unique risks of each business vertical.

This individual is also responsible for creating a feedback process with partners and marketing teams for proactive and continuous feedback driven improvements to overall lead quality.

The Fraud and Lead Quality Analyst position will take responsibility for data-driven management of our fraud management & lead quality assurance programs, using a data analytics skillset applied across multiple data repositories (Snowflake, Sumo Logic, etc.) including presentation of findings in business intelligence formats (Power

BI, Tableau). A successful candidate will partner with multiple business units to build an effective and customized fraud management & lead quality assurance program tailored to our unique business risks & requirements.

• Provides ongoing data-driven analytics on fraudulent activity to improve the efficacy and accuracy of our fraud detection and management program.
• Provides ongoing data-driven analytics on overall lead quality to improve the value of our core business and ensure productive long-term relationships with our partners.
• Use these analyses to make data-driven improvements to both fraud and quality assurance programs
• Work with vendors to continuously evaluate and improve the value proposition of purchased fraud/quality control products and services.
• Use API-based connectors to collect and transfer data from multiple sources to our data warehouse Snowflake.
• Once in Snowflake, write custom queries and perform necessary data manipulation to gather and organize this data and create live-view dashboards providing real-time monitoring of suspected fraudulent activity or other security data.
• Employs machine learning techniques to continually update and improve the accuracy and effectiveness of our fraud and quality assurance programs.
• Works in cross-functional capacity to address business needs and ensures our fraud management and quality assurance programs are tailored to the unique risks faced by different parts of the business.
• Monitors the fraud detection program for suspected organized fraud incidents and works with other parts of the business like the Customer Contact Center to identify and respond to fraud activity in a timely and efficient manner.
• Work with partner financial institutions to investigate and help remediate any concerns about fraud or lead quality in a timely and efficient manner.
• Maintains compliance with various 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 professional experience in fraud management or lead quality assurance required, preferably in the financial technology (Fin Tech) industry.
• Strong data analytics/data engineering skillset required, including demonstrated expertise using data warehouses such as Snowflake, logging technologies such as Sumologic, and business intelligence tools such as Tableau.
• Experience with fraud detection and management in a Fin Tech context, including knowledge of common fraud techniques, strongly preferred.
• Experience…