Machine Learning Engineer (ROA + LTV ML)

Join Affirm as a Machine Learning Engineer, where you'll develop and implement machine learning models to predict default likelihood and make approval decisions. Collaborate with engineering, credit, and product teams, and contribute to the future of credit decisioning. Enjoy a remote-first work environment, generous time off, and comprehensive health benefits.

About Affirm

Persistence, patience and a strong sense of responsibility – we build the decision making that enables consumers and partners to place their trust in Affirm!

Responsibilities

• Utiliser les données propriétaires d'Affirm et d'autres données tierces pour développer des modèles d'apprentissage automatique qui prédisent la probabilité de défaut.
• Collaborer avec les équipes d'ingénierie de la plateforme et du produit pour construire des systèmes de formation, de décision et de surveillance des modèles.
• Mettre en œuvre et mettre à l'échelle des pipelines de données, de nouvelles fonctionnalités et des algorithmes essentiels à nos modèles de production.

Requirements

• 2+ years of experience as a machine learning engineer or PhD in a relevant field
• Experience developing machine learning models at scale from inception to business impact
• 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 is a plus
• Experience using large scale distributed systems like Spark or Ray
• Experience using open source projects and software such as scikit-learn, pandas, NumPy, XGBoost, Kubeflow
• The ability to present technical concepts and results in an audience-appropriate way
• Strong engineering skills in Python and data manipulation skills like SQL
• Excellent written and oral communication skills and the capability to drive cross-functional requirements with product and engineering teams