Payments Risk Analyst, Push Payments

What you’ll be doing (ie. job duties):

Identify, investigate and mitigate fraudulent deposit activity
Implement logic targeting bad actors and high-risk behavior associated with unauthorized deposit activity across multiple regions
Review and respond to alerts regarding anomalous customer and transaction behavior
Measure fraud performance across payment methods, develop core metrics, and create dashboards to track and understand them
Proactively identify and close gaps in our monitoring
Own risk controls from end-to-end and scale processes to provide appropriate coverage as we expand our business
Own reporting processes and communication with relevant banking partners
Work with internal stakeholders in Product, Growth, Data Science and Engineering to develop and drive forward custom risk management strategies and techniques for different geographies
Use data to assess risk and make decisions impacting large segments of our customer population; effectively measure and assess associated tradeoffs using quantitative analysis
Synthesize data learnings into compelling stories and communicate them to Payments Risk leadership
What we look for in you (ie. job requirements):

4+ years relevant experience
2+ years fighting push payment fraud in an e-commerce or financial services environment
2+ years of experience in data analysis, working with databases, and querying (e.g., SQL, MySQL, etc).
BA / BS degree or equivalent practical experience
Strong knowledge of push payment processes, and fraud claim investigations
A passion for fighting fraud and abuse, and the curiosity to self-drive investigations, identify patterns, and find the root cause
Experience in data analyses using SQL
Experience with data visualization and storytelling using Looker, Tableau, SuperSet or other business intelligence platforms
Be able to independently create plans for analytics projects and build collaboration within the team
Demonstrate our core cultural values: clear communication, positive energy, continuous learning, and efficient execution
Nice to haves:

Understanding of statistical concepts and experience in applying them
Experience working with quantitative tools such as Python or R
Experience working with machine learning models
An understanding of blockchain analytics and/or fraud trends within the cryptocurrency ecosystem
PID: P56612