We've opened an office in Poland with a goal to hire a substantial team of talented engineers within the first year. Read more about our plans here.

The Merchant Risk Engineering team’s mission is to deliver a robust merchant approval and risk monitoring platform for the timely, transparent, and consistent assessment of merchant risk throughout the merchant lifecycle. This team works in close partnership with our product managers and risk teams to effectively onboard merchants and build automated risk tools in order to minimize losses post-onboarding. Affirm’s stated goal is to build the largest network as measured by the number of users and merchants; a strong merchant risk capability is key to growing the merchant side of the network equation.

We are looking for highly motivated senior engineers to help build this team in Poland. Come join us!

What You'll Do

• Design, develop, and deploy a platform for assessing the legitimacy of any merchant. Scale the platform to onboard millions of merchants while minimizing losses resulting from fraudulent merchants.
• Build tools for our Risk team to enable (1) prompt risk management (2) human-in-the-loop learning, and (3) control merchant fraud losses.
• Partner with Analyst, Data Science, and Product engineering teams to build production machine learning models; your models will decide which merchants we onboard to the Affirm platform in real time
• Develop our understanding of new data sources and how they may improve our existing processes
• Collaborate with other tech-leads, managers, and partners across Affirm's engineering, credit, risk, marketing, and analytics teams to understand our performance modeling strategies, the business drivers underlying those strategies, and drive requirements for new products
• Serve as a trusted advisor on the application and implementation of machine learning across Affirm

What We Look For

• B.S. with 8+ years of industry experience, M.S. with 7+ years, PhD with 6+ years, or equivalent experience
• Demonstrated experience designing real time systems and writing production-quality software
• Experience with the AWS technical stack and data infrastructure such as MySQL, Spark, Kubernetes, Docker, and Airflow
• Proficiency in machine learning with experience in areas such as gradient boosting, deep learning, recommendation systems, computational advertising, reinforcement learning, financial forecasting, time series analysis, anomaly detection, monte-carlo simulations, and Markov decision processes
• Strong programming skills in Python. Experience using frameworks for machine learning and data science like scikit-learn, pandas, numpy, XGBoost, TensorFlow, mllib
• Excellent written and oral communication skills including the capability to drive requirements with product and engineering teams and present technical concepts and results in an audience-appropriate way
• Ability to work efficiently both solo and as part of a team; willingness to learn new things and mentor others
• Passion to change consumer banking for the better, while developing a deeper understanding of applied machine learning