Applied Scientist

At Upstart, we’re united by a mission that matters: to radically reduce the cost and complexity of borrowing for all Americans. Every day, we bring creativity, experimentation, and advanced AI to reshape access to credit, helping millions move forward financially with clarity and confidence.

As the leading AI lending marketplace, we partner with banks and credit unions to expand access to affordable credit through technology that’s both radically intelligent and deeply human. Our platform runs over one million predictions per borrower using more than 3,000 signals, powering smarter, fairer decisions for...

We’re proudly digital-first, giving most Upstarters the flexibility to do their best work from wherever they thrive, alongside teammates across 80+ cities in the US and Canada. Digital-first doesn’t mean distant. We’re intentional about in-person connection through team onsites, planning sessions, and moments that s...

Graduate degree in mathematics, applied mathematics, statistics, physics, econometrics, operations research, computer science, or a related quantitative field.
0–2 years of experience conducting machine learning, statistical modeling, or applied quantitative research in an academic or industry setting.
Experience developing and evaluating machine learning or statistical models using Python.
Demonstrated knowledge of probability, statistics, and machine learning methods.
Experience designing experiments or validation analyses to assess model accuracy, reliability, or predictive performance.
PhD in a quantitative field.
Knowledge of supervised learning, model evaluation, and feature engineering techniques.
Experience working with large or complex datasets and translating research concepts into implemented solutions.
Ability to balance research velocity with analytical rigor, model reliability, and responsible decision-making.
Strong written and verbal communication skills, with the ability to clearly explain technical concepts and collaborate effectively with cross-functional teams and stakeholders from diverse backgrounds.