Upstart

Manager, Machine Learning

Upstart United States

About Upstart

Upstart is a leading AI lending marketplace partnering with banks and credit unions to expand access to affordable credit. By leveraging Upstart's AI marketplace, Upstart-powered banks and credit unions can have higher approval rates and lower loss rates across races, ages, and genders, while simultaneously delivering the exceptional digital-first lending experience their customers demand. More than two-thirds of Upstart loans are approved instantly and are fully automated.

Upstart is a digital-first company, which means that most Upstarters live and work anywhere in the United States. However, we also have offices in San Mateo, California; Columbus, Ohio; and Austin, Texas.

Most Upstarters join us because they connect with our mission of enabling access to effortless credit based on true risk. If you are energized by the impact you can make at Upstart, we’d love to hear from you!

The Team and Role

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.

As Manager of Machine Learning, you will lead a team of 2 research scientists and a data scientist on our Small Dollar Lending product, an unsecured personal lending product for small, short-term loans. The team focuses on modeling credit risk and operational costs, and making corresponding underwriting and pricing decisions.

  • 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 or West Coast time zones.
  • Travel Requirements - This team has regular on-site collaboration sessions. ML Managers can anticipate working in either HQ 3 days/week 6 times/year. Since this is a leadership position, a few additional travel dates may be possible for onsite collaborations with other teams. If you need to travel to make these meetups, Upstart will cover all travel related expenses.

How you’ll make an impact:

  • Lead your team to apply state-of-the-art machine learning methods (e.g. recurrent neural networks, gradient boosting methods for survival time prediction, model ensembling and stacking) to a critical prediction problem (credit risk) where machine learning is not widely applied and the optimal solutions are not known.
  • Search for new variables, either internal to Upstart, or from external vendors, that can improve our underwriting models’ performance.
  • Work with the Small Dollar Lending team to identify opportunities for new ML models to be used in credit decisioning.
  • Along with your team, assume responsibility for the performance of Upstart’s loan originations for the Small Dollar Lending product.

Minimum qualifications:

  • Bachelor’s degree in quantitative area of study
  • 1+ years as a data science or machine learning people manager or tech lead
  • Understanding of machine learning models and statistical methods
  • Coding proficiency, preferably in Python
  • Excellent quantitative critical thinking skills

Preferred qualifications:

  • Advanced degree in quantitative area of study such as statistics, operations research, finance, mathematics, or related field
  • Prior experience managing teams that build machine learning models, prepare them for production, and make large, direct contributions to a business’ profitability
  • 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

At Upstart, your base pay is one part of your total compensation package. The anticipated base salary for this position is expected to be within the below range. Your actual base pay will depend on your geographic location–with our “digital first” philosophy, Upstart uses compensation regions that vary depending on location. Individual pay is also determined by job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

In addition, Upstart provides employees with target bonuses, equity compensation, and generous benefits packages (including medical, dental, vision, and 401k).

United States | Remote - Anticipated Base Salary Range

$174,900—$242,000 USD

Upstart is a proud Equal Opportunity Employer. We are dedicated to ensuring that underrepresented classes receive better access to affordable credit, and are just as committed to embracing diversity and inclusion in our hiring practices. We celebrate all cultures, backgrounds, perspectives, and experiences, and know that we can only become better together.

If you require reasonable accommodation in completing an application, interviewing, completing any pre-employment testing, or otherwise participating in the employee selection process, please email candidate_accommodations@upstart.com

https://www.upstart.com/candidate_privacy_policy

  • Seniority level

    Mid-Senior level
  • Employment type

    Full-time
  • Job function

    Science and Engineering
  • Industries

    Financial Services

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