Staff Data Scientist

About Upstart

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 1,800 signals, powering smarter, fairer decisions for millions of customers. But the numbers only hint at the impact. Every idea, every voice, and every contribution moves us closer to a world where credit never stands between people and their financial progress.

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 spark creativity and trust. And whether you choose to work primarily from home or collaborate in-person from one of our offices in Columbus, Austin, the Bay Area, or New York City (opening Summer 2026), you’ll have the support to work in the way that works best for you.

If you’re energized by tackling meaningful problems, excited to innovate with purpose, and motivated by work that truly matters, we’d love to hear from you.

The Team:

Upstart’s Personal Loans Underwriting and Credit Analytics team is responsible for building, improving, and monitoring Upstart’s core underwriting model. This machine learning model powers our decisions on which loans to approve and at what rates, directly influencing borrower access to credit, investor returns, and overall company performance. Because underwriting sits at the heart of Upstart’s marketplace, the team’s work is central to the company’s long-term success.

As a Staff Data Scientist at Upstart, you will own the monitoring and performance analytics of our Personal Loans underwriting models and credit portfolio. This role provides regular visibility to senior leadership and plays a key role in shaping data-driven decisions at the highest levels of the organization.
In addition to leading recurring reporting and performance tracking, this role requires strong analytical curiosity and investigative rigor. You will proactively monitor portfolio and model performance, identify emerging trends, diagnose unexpected outcomes, and recommend actionable treatments. This role is well-suited for someone who enjoys going beyond standard reporting to conduct deep analytical investigations and drive meaningful business impact in a production machine learning environment.

How you’ll make an impact

• Lead end-to-end monitoring of underwriting model performance and outcomes, ensuring models are behaving as expected across risk segments and macroeconomic conditions; translate model metrics into clear business implications
• Detect shifts in approval rates, loss performance, borrower behavior, or model predictions, and use analytical methods to investigate drivers of change, distinguish signal from noise, and quantify business impact
• Apply statistical techniques to assess A/B tests, model launches, and natural experiments, and provide clear recommendations grounded in causal reasoning and quantitative evidence
• Develop and maintain automated reporting, monitoring frameworks, and workflows that ensure timely, accurate visibility into model performance at scale

Minimum Qualifications 

• Master’s degree in a quantitative field (e.g., Statistics, Mathematics, Economics, Finance, Operations Research, Physics, or related field)
• 6+ years of experience in analytics, data science, or a related quantitative field
• Proficiency in Python (Pandas/Numpy) and SQL
• Strong analytical and first-principles thinking, with the ability to tackle complex and ambiguous problems
• Strong communication, presentation, and collaboration skills, with the ability to clearly articulate complex analytical concepts to diverse audiences

Preferred Qualifications

• PhD in a quantitative field (e.g., Statistics, Mathematics, Economics, Finance, Operations Research, Physics, or related)
• Experience in consumer finance, credit risk, or lending analytics
• Experience working with production machine learning systems or underwriting models

Position location This role is available in the following locations: Remote 

Travel requirements As