Staff Research Scientist - Growth

The Team: 

Upstart’s Growth Team  engages in marketing and borrower acquisition through direct mail (DM) campaigns and targeted loan offers on partner sites, leveraging machine learning to drive growth. The Growth ML team develops models to optimize borrower targeting, predict conversion probabilities, and refine pricing strategies across these channels. We’re also beginning to explore a new concept known as “always on underwriting.” The idea is to continuously evaluate borrowers’ credit worthiness and determine what loan products are available at any given time, and then proactively make those offers to them when we determine it’s the right time to do so. 

As a Staff Research Scientist  at Upstart, you will help to build the foundational models that power always-on underwriting across our product portfolio. You will understand the core underwriting model for each product and build models that can approximate their behavior using less data and/or somewhat outdated data. You will help determine whether/when new data needs to be gathered before an offer can be made, and when an “always on” offer should be honored vs. updated based on new information. 

How you’ll make an impact:

• Launching an entirely new customer experience that will transform Upstart from a “one-time” option to get a loan at a discrete point in time to a relationship based model in which borrowers are continuously made aware of credit options that meet their needs.
• Collaborate with and influence partner teams, ensuring that data-driven recommendations lead to strategic business decisions.
• Build scalable models and associated metrics and monitoring  processes..
• Quickly prototype and test  new models that can improve accuracy  and borrower experience with always-on offers. 

Minimum Qualifications: 

• 5+ years of experience building and deploying ML models in a production environment
• Strong academic credentials with a master's degree in statistics, mathematics, economics, computer science, or other quantitative areas of study
• Programming skills in Python 
• Proficiency in a broad array of mathematical, statistical learning and machine learning concepts and applications
• Ability to proactively and effectively communicate results and methodologies to both technical and non-technical stakeholders 
• Strong sense of intellectual curiosity balanced with humility, drive and teamwork
• Experience building performant and large scale ML models at a tech company
• Experience working as part of a diverse, cross-functional team.

Preferred Qualifications:

• 7+ years of experience building and deploying ML models in a production environment
• PhD in statistics, mathematics, economics, computer science, or other quantitative areas of study
• Experience building and launching zero-to-one product
• Full-stack expertise with all steps of the modeling process from ideation to productionalizing code
• Deep expertise in statistical modeling and machine learning
• Knowledge of MLops, pipelines, and engineering architecture 

Time zone requirements The team operates on the East/West coast time zones.

Travel requirements As a digital first company, the majority of your work can be accomplished remotely. The majority of our employees can live and work anywhere in the U.S but are encouraged to to still spend high quality time in-person collaborating via regular onsites. The in-person sessions’ cadence varies depending on the team and role; most teams meet once or twice per quarter for 2-4 consecutive days at a time.

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