Join Upstart as a Remote Applied Scientist, focusing on innovative machine learning to enhance credit decisioning. Utilize cutting-edge research to drive impactful improvements in unsecured lending models.

As an Applied Scientist on the Unsecured Underwriting Machine Learning team, you will enhance Upstart’s core models using advanced machine learning techniques. This role spans research, implementation, and evaluation of predictive improvements aimed at optimizing credit decisions. Collaborate closely with Engineering teams to translate findings into scalable solutions.

Key Responsibilities:
• Research advanced machine learning approaches for underwriting models
• Design and evaluate model enhancements rigorously
• Analyze model performance and impact on decisioning




• Collaborate with Engineering for implementation and deployment
• Create clear recommendations and methodologies for production

Requirements:
• Graduate degree in quantitative field
• 2+ years of machine learning experience
• Proficient in Python and statistical modeling
• Solid knowledge of statistics and experimental design
• Capable of effective cross-functional collaboration

Leverage your expertise in machine learning and statistical modeling to drive Upstart’s mission of revolutionizing access to credit through data-driven insights.
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📌 Remote Applied Scientist at Upstart (Ontario)
🏢 Upstart
📍 Ontario