Affirm is looking to optimize the flow of loan opportunities across its owned properties by designing, developing, and deploying advanced machine learning models and tools that support portfolio management actions, balancing key business metrics such as unit economics, product growth, and user experience.
Requirements
- Proficiency in machine learning techniques including Generalized Linear Models, Gradient Boosting, Deep Learning, and Probabilistic Calibration.
- Strong engineering skills in Python and data manipulation skills such as SQL.
- Experience delivering major system features, components, or deprecating existing functionalities through comprehensive technical and execution plans.
- Ability to write high-quality, maintainable, and well-documented code that facilitates collaboration and reuse.
- Comfortable working across different levels of system architecture, from low-level language idioms to large system design.
- Proven track record of gathering and iterating on feedback from engineering and cross-functional teams to drive impact.
Responsibilities
- Define and execute the technical strategy for the ML portfolio team, aligning with broader business objectives and product roadmaps.
- Develop and optimize machine learning models to support portfolio management, risk assessment, and decision-making processes.
- Collaborate with cross-functional teams including product management, design, and analytics to deliver scalable and sustainable solutions.
- Implement operational best practices, including monitoring, alerting, testing, and incident response protocols to ensure system reliability and availability.
- Establish and uphold high standards for code quality, system design, and documentation through code reviews and technical leadership.
- Lead efforts to improve existing systems, deprecate outdated functionalities, and introduce new features that enhance business value.
- Stay current with advancements in machine learning, data engineering, and fintech to continuously improve Affirm’s ML capabilities.
Other
- 8+ years of industry experience.
- Relevant PhD can count for up to 2 years of experience.
- Domain knowledge in credit risk, portfolio management, learning to rank, and personalization is a plus.
- Excellent verbal and written communication skills to facilitate effective collaboration within a global engineering environment.
- Equivalent practical experience or a related Bachelor’s degree is acceptable.
