Applyπ Canada
π§ Full-Time
πΈ 125000 - 175000 CAD per year
π Fintech
π’ Company: Affirm
- 2+ years of experience as a machine learning engineer or PhD in a relevant field.
- Proficiency in machine learning, with experience in gradient boosting, online learning, and deep learning.
- Domain knowledge in fraud risk is a plus.
- Strong programming skills in Python.
- Experience with large-scale distributed systems like Spark and Ray.
- Experience with machine learning frameworks such as scikit-learn, pandas, numpy, xgboost, and pytorch.
- Excellent communication skills and ability to drive cross-functional requirements.
- Ability to present technical concepts in audience-appropriate ways.
- Persistence, patience, and a strong sense of responsibility.
- Use proprietary and third-party data to develop machine learning models that predict likelihood of fraud.
- Partner with the ML platform team to build fraud-specific ML infrastructure.
- Research groundbreaking solutions and develop prototypes for fraud decisioning.
- Implement and scale data pipelines, new features, and algorithms essential to production models.
- Collaborate with engineering, fraud, and product teams to define new product requirements.
- Develop fraud models to maximize user conversion while minimizing losses.
PythonMachine LearningNumpyPyTorchAlgorithmsPandasSparkCommunication Skills
Posted 2024-10-28
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