Staff Machine Learning Engineer (ML Portfolio)
AffirmSalary not specified
- Full Time
- Expert & Leadership (9+ years)
Not SpecifiedCompensation
Junior (1 to 2 years)Experience Level
Full TimeJob Type
UnknownVisa
Financial Technology, Credit Risk, LendingIndustries
Requirements
Candidates should have 3+ years of professional experience in developing and implementing credit ML models or systems within the banking or FinTech industry, an educational background in Computer Science, Engineering, Mathematics, or a related field, and proficiency in Python, PostgreSQL, Java/Scala. Strong knowledge of supervised and unsupervised learning, deep learning, reinforcement learning, and ensemble methods is required, along with familiarity with database management systems and SQL databases. Japanese bilingual skills are ideal.
Responsibilities
The Machine Learning Engineer will design and implement credit ML models and systems, ensuring robust and scalable solutions; develop end-to-end ML pipelines for credit modeling, including data collection, preprocessing, model training, and deployment; collaborate with data scientists and software engineers to integrate ML models into production environments, enhancing lending systems; and utilize cloud platforms (AWS preferred, GCP, Azure) to scale ML solutions, manage resources, and optimize costs.
Skills
Machine Learning
Credit Modeling
Risk Prediction
ML Pipelines
Data Preprocessing
Model Deployment
Cloud Platforms (AWS, GCP, Azure)
PayPal
Digital payments platform for various clients
About PayPal
PayPal offers a digital payments platform that allows users to conduct online transactions, mobile payments, and peer-to-peer transfers. It generates revenue primarily through transaction fees charged to merchants and provides various services for individual consumers, small to medium-sized businesses, and large enterprises. PayPal distinguishes itself from competitors by offering a wide range of secure financial services tailored to different client needs. The company's goal is to create a convenient and secure digital payments experience for all users.
Key Metrics
San Jose, CaliforniaHeadquarters
1998Year Founded
$188.7MTotal Funding
IPOCompany Stage
Fintech, Financial ServicesIndustries
10,001+Employees