Research Scientist

Upstart

2d•Remote

About The Position

Upstart is the 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 80% of borrowers are approved instantly, with zero documentation to upload. 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; Austin, Texas; and New York City, NY (opening Summer 2026). 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! At Upstart, our mission is to expand access to credit using advanced machine learning models that better evaluate true risk. As part of this, our teams focus on developing models across various verticals, including Growth marketing, Auto Loans, and Personal Loans Underwriting. These teams are critical to the success of Upstart, directly impacting our customer acquisition efforts and revenue generation through predictive modeling, innovative algorithms, and cross-functional collaboration. Our Machine Learning (ML) Teams work on creating and deploying production models that power key aspects of Upstart’s business: Growth: Models that predict conversion probabilities and prioritize high-potential prospects for outbound marketing. Auto Loans: Models that underwrite all auto loans, assessing true borrower risk based on innovative features and methodologies. Personal Loan Underwriting: Models that evaluate every applicant’s risk, having a direct impact on Upstart’s core business. As a Research Scientist, you will have the opportunity to work in one of these highly specialized teams, contributing to the development and deployment of business-critical models, optimizing marketing strategies, underwriting processes, and enhancing business metrics.

Requirements

Bachelor’s degree in a scientific or quantitative discipline (e.g., Math, Physics, Computer Science, Statistics, Economics, Operations Research).
2+ years of experience in Machine Learning or a similar field.
Proficiency in Python or other programming languages.
Strong understanding of statistical, probability, and machine learning theory.
Full-stack expertise in the modeling process from ideation to production, OR deep expertise in either statistical modeling or machine learning.
Ability to break down complex tasks into smaller steps and make the right tradeoffs to deliver projects on time.
Ability to communicate technical concepts effectively to non-technical stakeholders.
Strong sense of intellectual curiosity, humility, and teamwork.

Nice To Haves

Master’s degree or PhD in a quantitative discipline (e.g., Math, Physics, Economics, Computer Science, Statistics, Operations Research).
Deep expertise in Python and experience with machine learning frameworks.
Experience leading or mentoring junior members in a technical team.
Proficiency in building and deploying machine learning pipelines and engineering architecture.
Strong critical thinking skills and ability to develop testable hypotheses.
Proven ability to meet high standards in terms of quality and velocity with minimal direction.

Responsibilities

Research and develop new machine learning models to enhance the accuracy of predictions in borrower risk, marketing conversions, or underwriting processes.
Design, prototype, and deploy models to production, ensuring robust and scalable implementations.
Collaborate cross-functionally with engineers, product managers, and marketing specialists to experiment with and optimize models for business outcomes.
Evaluate the performance of models, interpret their impact on business metrics, and present actionable insights to stakeholders.
Continuously explore novel algorithms and methodologies to keep Upstart’s ML systems at the cutting edge of technology.
Mentor junior team members and contribute to the development of a high-quality, production-ready codebase.

Benefits

Competitive Compensation (base + bonus & equity)
Comprehensive medical, dental, and vision coverage with Health Savings Account contributions from Upstart
Generous 401(k) plan with Upstart matching $2 for every $1 contributed, up to $15,000 per year
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