The Team
Upstart’s Machine Learning team has a direct impact on our company's success. The team consists of research scientists, data scientists, and machine learning engineers who build and enable our core production models. The fundamental goal of the Machine Learning team is to explore new models and new data sets that can improve the accuracy of our models. With this goal comes near-limitless challenges to tackle, and that is one of the reasons why Upstart is such a unique opportunity.
The macro, metrics, and monitoring team, a part of Upstart machine learning’s personal loan underwriting team, is focused on monitoring and improving the performance of our underwriting models, particularly with respect to portfolio- and macro-level, rather than loan-level, performance. The team researches improvements to underwriting, including time-series portfolio-level predictions, adjustments to machine learning underwriting models to improve. The team also builds portfolio management models, researchers model performance metrics, and builds dashboards and reports on underwriting model performance.
As a Manager of Machine Learning, you will lead the macro, metrics, and monitoring team, managing data scientists and research scientists. We are also open to hiring an analytics-focused manager for the data scientists on the team. The manager will be directly responsible for ensuring Upstart’s personal loan underwriting models are originating loans that will achieve our lending partner’s target rates of return.
Position location: This position is available in the following locations: San Mateo, California; Columbus, Ohio; Austin, TX; or Remote USA
Time zone requirements: The team operates on the East/West coast time zones.
Travel requirements: This team has regular onsite collaboration sessions. These occur X days per Quarter at the San Mateo or Columbus offices. If you need to travel to make these meetups, Upstart will cover all travel related expenses.
How you’ll make an impact:
Minimum qualifications:
Preferred qualifications:
What you'll love:
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