Research Scientist, Personal Loans

The Team:

Upstart’s Machine Learning team has a direct impact on our company's success. The team consists of Research Scientists, Data Scientists, ML Engineers and other highly specialized roles. As a whole, the Machine Learning team builds, enables and evaluates our core production models.

Because our challenges are so new, members of our Machine Learning team need strong creative problem-solving skills and the technical background to implement solutions. Our research environment affords team members the opportunity to utilize a variety of statistical and machine learning methods with the freedom and encouragement to pursue alternative approaches to solving problems. Whether developing new products or identifying novel approaches to core models, we are continuously seeking the next big ideas to move our business forward.

This role sits on the Personal Loans, Underwriting team. This is the team that is directly responsible for building and maintaining the models that evaluate the true risk of every applicant. The Personal Loan Underwriting ML team is responsible for researching and building these models and therefore have a direct impact on our company’s success.

The Role:

As a Research Scientist with Upstart, you'll enjoy a fast-paced environment with a focus on productionalizing, deploying and training machine learning models. You’ll also have an opportunity to work alongside a talented team that values curiosity, humility, drive and teamwork.

• Position Location - This role is available in the following locations: Columbus, Austin, San Mateo, or Remote
• Time Zone Requirements - This team operates on either the East, Central, or West Coast time zones.
• Travel Requirements - This team has regular on-site collaboration sessions six times annually split between our San Mateo or Columbus office locations. If you need to travel to make these meetups, Upstart will cover all travel related expenses.

What we’re looking for:

• Strong academic credentials with a master's degree in statistics, mathematics, economics, physics, operations research, computer science, or other quantitative areas of study; Ph.D. preferred
• Programming skills in Python
• Full-stack expertise with all steps of the modeling process from ideation to productionalizing code; OR deep expertise in either statistical modeling or machine learning
• Proficiency in a broad array of mathematical, statistical learning and machine learning concepts and applications
• Knowledge of machine learning, pipelines and engineering architecture
• Detailed understanding of building good technical solutions; ability to convert ideas into testable hypotheses and/or next steps
• Ability to meet team standards with respect to quality and velocity with minimal help or direction from peers
• For more complex tasks, ability to break down problems into smaller tasks, and use them to estimate the timeline of executing a larger initiative. Willingness to make the right tradeoffs when needed to deliver projects on time.
• Proactively communicate to stakeholders and teammates with ability to contextualize technical results
• Strong sense of intellectual curiosity balanced with humility, drive and teamwork
• Numerically-savvy and smart with ability to operate at a speedy pace
• Enthusiasm for and alignment with Upstart’s mission and values

What you’ll love:

• Competitive Compensation (base + bonus & equity)
• Comprehensive medical, dental, and vision coverage
• Personal Development and Technology & Ergonomic Budgets
• Life insurance and disability benefits
• Clubs and Activities (Game Nights, Fitstarters, Superwomen, Book Club, Investing Club, Money Discussions, Photography Club and Basketball teams)
• Generous vacation policy
• 401(k) and Employee Stock Purchase Plan (ESPP)
• Catered lunches + snacks & drinks

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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