Principal Data 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...

8+ years of experience in data science or quantitative roles with direct impact on product or business strategy.
Demonstrated mastery of experimental design and A/B testing, with rigorous experience designing and interpreting experiments and translating findings into meaningful business actions.
Deep statistical expertise, including causal inference methods, with the ability to select and apply the right method to ambiguous business problems and derive causal insights rather than surface-level correlations.
Strong coding experience in Python or equivalent, with a demonstrated ability to build technical tools that create leverage across the organization rather than just executing ad hoc analyses.
Track record of partnering with non-technical stakeholders to translate data into actionable business decisions, not just delivering analyses.
Comfort operating in ambiguous environments where the right questions aren't predetermined, and the ability to shape direction through thoughtful inquiry.
Exceptional communication skills, demonstrated ability to move fluidly between strategic questions and tactical details, and excellence in translating complex technical bodies of work into clear narratives.
Exposure to ML applications and ability to partner effectively with ML/data science teams on technical challenges.
Familiarity with personalization, recommendation systems, or matching algorithms.

 
Experience with at least one of the following is highly preferred: forecasting, spend allocation optimization, marketing incrementality, or attribution.