Upstart Inc. San Mateo , CA 94401
Posted 5 days ago
Machine Learning Team:
Upstart's Machine Learning team has a direct impact on our company's success. The team consists of full-stack applied science generalists as well as specialists in research, data science, statistical modeling and machine learning. 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.
Servicing Team:
World class servicing is a win-win. Lenders and investors will participate more in the case of good outcomes; borrowers who pay back have better credit scores and more access to credit; and most importantly, knowing that loans will be serviced in a world class way, Upstart can approve more borrowers, growing our business and our impact.
Servicing is the core of Upstart's relationship to borrowers, where they will spend 99% of their lives with us. They are also most likely to interact with our team when they're frazzled, distressed, or just plain broke. In this team, you'll balance accountability with compassion, and above all create frictionless, superb experiences. We're asking people to pay us, after all - the least we can do is to make it easy!
Ultimately, this team is responsible for not only predicting borrower outcomes, but also shaping them. No companies have solved this problem well, and it has practically infinite upside. The opportunity is breathtaking, and our ML edge could make all the difference.
You will be the second Research Scientist to join our Servicing Machine Learning team. Servicing at Upstart has enormous opportunities, because of lack of historical investments. But also because of lack of historical investment, Servicing needs an experienced hire that is not only independent technically, but can also think through business issues, work with cross-functional teams, and set up Servicing for success in the long run.
How you'll make an impact:
Improve Upstart's loan performance using experimentation and machine learning to make optimal loan servicing decisions.
Establish a framework for running and evaluating servicing experiments, for example, establishing metrics for evaluating the success of servicing interventions.
Work with product, engineering, and operations to ensure our decisioning system and data storage is transparent and provides everything needed for analysis of models and experiments.
Build machine learning models to predict risk, for example of probability of rolling from delinquency to charge off.
Minimum qualifications:
Bachelor's degree in quantitative area of study
Understanding of machine learning models and statistical methods
Coding proficiency, preferably in Python
Excellent quantitative critical thinking skills
Excellent communication skills
Preferred qualifications:
4+ years of experience in machine learning or adjacent field.
Prior experience leading machine learning or data science initiatives from end-to-end, working with cross functional stakeholders, and 0-to-1 projects.
Advanced degree in quantitative area of study such as statistics, economics, operations research, finance, mathematics, or related field.
Consumer lending knowledge and/or experience within an ML-centric technology company is a plus.
What you'll love:
Competitive compensation (base + bonus & equity)
Comprehensive medical, dental, and vision coverage with Health Savings Account contributions from Upstart
401(k) with 100% company match up to $4,500 and immediate vesting and after-tax savings
Employee Stock Purchase Plan (ESPP)
Life and disability insurance
Generous holiday, vacation, sick and safety leave
Supportive parental, family care, and military leave programs
Annual wellness, technology & ergonomic reimbursement programs
Social activities including team events and onsites, all-company updates, employee resource groups (ERGs), and other interest groups such as book clubs, fitness, investing, and volunteering
Catered lunches + snacks & drinks when working in offices
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