Machine Learning Engineer (Core ML)
Description For Machine Learning Engineer (Core ML)
Our client, a pioneer in reshaping consumer credit using innovative technology, is committed to reducing capital costs. They strongly believe in universal access to capital, crucial in today's capital-based economy, with over $1 trillion in unsecured credit card revolving balances.
The company has introduced a new asset-backed credit card, securing equity in homes, cars, and other assets. This innovation allows them to offer remarkably low APRs to consumers. Their flagship product boasts the world's lowest APR credit card, aiming to change the credit paradigm.
Backed by substantial equity funding of over $125 million, the company comprises a well-capitalized team of technology (Microsoft, Facebook) and finance (Square, Discover, CapitalOne, Goldman) experts. They have top-tier investors like Founders Fund, Khosla Ventures, Caffeinated Capital, Max Levchin, NYCA, and Sequoia, and recently secured Series C funding.
As a Machine Learning Engineer (Core ML), you will focus on crafting intricate financial workflows, especially regarding the facilitation of credit lines and the retrieval of payments from individuals. Key areas of emphasis include:
- Response Modeling
- Risk Modeling
- Building models to estimate income and employment stability
- Designing Pricing Models
- Creating Anti-Fraud Models
- Automating human operations for increased efficiency
Join this innovative team and contribute to transforming consumer credit with cutting-edge machine learning technologies.
Responsibilities For Machine Learning Engineer (Core ML)
- Develop response modeling algorithms
- Create risk modeling systems
- Build models to estimate income and employment stability
- Design pricing models
- Develop anti-fraud models
- Automate human operations for increased efficiency
Requirements For Machine Learning Engineer (Core ML)
- Experience in machine learning and data science
- Knowledge of financial workflows and credit systems
- Proficiency in developing and implementing ML models
- Understanding of risk assessment and fraud detection
- Experience with automation and efficiency optimization
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