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Senior Machine Learning Engineer (Portfolio ML)
Affirm • Ready to make a difference?
About Affirm
Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest.
About the Role
Affirm’s Portfolio ML team is looking for an exceptional machine learning engineer to build the next generation of credit opportunity management models. Sitting at the intersection of credit policy and consumer product, this role will work within a highly cross-functional and diverse set of workstreams that contribute directly to profitability. From choosing which users to engage for repeat, finding the optimal value propositions to present them, and owning unit economics libraries, the Portfolio ML team’s focus spans the entire customer lifecycle including re-engagement. The team is relatively new and has a number of greenfield initiatives in its mandate, an exceptional group of ICs, and strong Product leaders in partnership.
What You'll Do
- Use Affirm’s proprietary and other third-party data to develop machine learning models that manage and optimize the flow of loan opportunities across Affirm-owned and -operated properties.
- Partner with platform and product engineering teams to build model training, decisioning, and monitoring systems.
- Research groundbreaking solutions and develop prototypes that drive the future of portfolio decisioning at Affirm.
- Implement and scale data pipelines, new features, and algorithms that are essential to our production models.
- Collaborate with the engineering, credit, and product teams to define requirements for new products.
What We Look For
- Proficiency in machine learning with experience in areas such as Generalized Linear Models, Gradient Boosting, Deep Learning, and Probabilistic Calibration. Domain knowledge in credit risk, portfolio management, learning to rank, and personalization is a plus.
- Strong engineering skills in Python and data manipulation skills like SQL.
- Experience using distributed systems like Spark or Ray is a plus.
- Experience using open-source projects and software such as scikit-learn, pandas, NumPy, XGBoost, Kubeflow.
- Excellent written and oral communication skills and the capability to drive cross-functional requirements with product and engineering teams.
- The ability to present technical concepts and results in an audience-appropriate way.
- Persistence, patience, and a strong sense of responsibility – we build the decision-making that enables consumers and partners to place their trust in Affirm!