About the role:
Define data sources and data elements required to effectively understand our fraud vectors.
Have a clear understanding of each vendor with whom we work, their function, and the data they make available to us.
Write and optimize complex SQL queries to extract, transform, and analyze data from multiple databases.
Work with data engineers to improve data pipelines and ensure accurate fraud monitoring datasets.
Maintain data integrity and ensure proper documentation of fraud-related datasets.
Develop and maintain fraud risk measures and dashboards.
Follow the full data journey as it relates to the payment/fraud/business operations environment, including:
Identifying issue(s) and potential areas of improvement
Determining the correct data sets to evaluate
Querying and validating the data
Working with other departments to enhance the data with otherwise missing information
Converting the data into a usable, human-readable form
Extrapolating root causes and recommended solutions
Identifying ROI, cost/benefit, and creating a business case for the solutions
Preparing the information and presenting it to leadership
Ensure appropriate Key Risk Indicators are developed and maintained; identify and clearly articulate gaps.
Collaborate with Payments team and Business teams to incorporate emerging threats into our acquisition and account management strategies, reviewing partner and marketing agreements to identify vulnerabilities.
Monitor, analyze, and investigate transactions, customer accounts, and financial activities to identify potential fraudulent patterns or anomalies.
About you:
Minimum of 4+ years of experience in fraud analysis, or related data-centered roles, with a focus on digital goods, ideally software.
Experience with fraud detection vendors (e.g. Signifyd, Bolster, Arkose, others).
Familiarity with fraud detection systems, payment risk tools, or chargeback analysis.
Proficiency in data analysis and tools such as SQL, Databricks/Mosaic, PowerBI. Advanced Excel knowledge (pivot tables, query functions, visualizations, etc.).
Ability to present complex information clearly, resulting in influencing senior leaders. Consistent follow up, execution abilities are key.
Proven ability to work collaboratively in a fast-paced, cross-functional environment.
Experience with AI tools for building dashboards and analyzing complex datasets is a plus.
Experience working in subscription-based or digital commerce environments.
Experience analyzing affiliate marketing fraud, payment fraud, or account abuse.
Knowledge of machine learning techniques for fraud detection is a plus.
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