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!
Upstart aims to expand access to credit based on true risk. As part of this mission, Upstart actively engages in marketing and borrower acquisition efforts to attract new customers. One key strategy involves direct mail (DM), an outbound marketing channel aimed at educating consumers about Upstart via physical mail and encouraging them to take out a loan.
Upstart’s Machine Learning, Growth Direct Mail team develops advanced DM models that predict conversion probabilities and effectively prioritize prospects. This team significantly contributes to Upstart's revenue and is integral to its overall success.
As a Staff Research Scientist on this team, you will play a crucial role in advancing direct mail campaign effectiveness through cutting-edge machine learning techniques.Your responsibilities will include participating in research and development initiatives to innovate and fine-tune predictive models that accurately forecast conversion probabilities and prioritize prospects. Coordinate and run prospects selection for direct mail campaigns. Collaborating closely with cross-functional teams, you will design and implement experiments to optimize campaign outcomes and enhance ROI. Your role will encompass exploring novel algorithms and methodologies, assessing their impact on revenue metrics, and propose innovative strategies for leveraging machine learning to enhance Upstart’s marketing strategies.
Position location: This role is available in the following locations: Remote
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.
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 USDUpstart 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 work@tuhustle.com