Machine Learning Engineer
Hang- Full Time
- Senior (5 to 8 years)
Candidates should possess a strong understanding of machine learning concepts, including Generalized Linear Models, Gradient Boosting, Deep Learning, and Probabilistic Calibration, along with proficiency in Python and SQL. Experience with distributed systems such as Spark or Ray and familiarity with open-source tools like scikit-learn, pandas, NumPy, XGBoost, and Kubeflow is preferred, and domain knowledge in credit risk is a plus. Excellent written and oral communication skills, including the ability to drive cross-functional requirements, and presentation skills are also required.
As a Machine Learning Engineer, the role involves developing machine learning models to predict default likelihood and make approval/decline decisions, partnering with engineering teams to build model training and decisioning systems, researching and prototyping groundbreaking solutions for credit decisioning, implementing and scaling data pipelines and algorithms, and collaborating with engineering, credit, and product teams to define requirements for new products.
Provides buy now, pay later financing solutions
Affirm offers point-of-sale financing solutions as an alternative to traditional credit cards. It allows consumers to make purchases and pay over time through installment plans, often without hidden fees or deferred interest. Affirm partners with merchants to integrate its payment solutions into online and in-store shopping experiences, using user-friendly plugins and APIs. The company generates revenue from interest and fees on loans to consumers, as well as fees from merchants for offering its financing options. Affirm also provides a merchant dashboard for transaction processing and promotional tools to help businesses market these financing options effectively. The goal of Affirm is to empower consumers with flexible payment options while providing value to merchants in the e-commerce and retail markets.