Staff Data Analyst, Servicing
UpstartUnited States | RemoteUp to $15kPosted 4 April 2026
Job Description
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 Servicing Analytics team plays a critical role of providing analytical capability for Upstart's servicing functions to enable data-driven decision making. We leverage our analytical and technical skills to support our partners with a multitude of services..
As the Staff Data Analyst on the Servicing Analytics team, you will play a pivotal role in influencing Upstart’s success. Partnering closely with our Servicing product management, operations, engineering, and ML teams, you’ll work directly with key stakeholders, helping drive understanding, insights, decision-making, and data infrastructure relating to the development, optimization, and enhancement of our recoveries and collections strategy. You’ll contribute to key areas such as identifying areas of opportunity via business reviews with leaders and product experiments, and driving operational efficiency. This role involves conducting in-depth analyses, building business intelligence pipelines, designing A/B tests, and collaborating with cross-functional teams to drive impacts.
How you’ll make an impact
Lead the development of analytical capabilities to support servicing initiatives and drive efficiency improvements.Create regular executive level presentations to communicate findings and strategic recommendations. Design experiments and conduct quantitative analysis to test hypotheses about our users and the way they interact with our servicing initiatives, and collaborate with partners to prioritize the right problems and opportunities. Collaborate with analytics engineering and software engineering to continuously up-level our servicing data capabilities, making new data available as the business expands, and accelerate time to insights. Develop and maintain business intelligence tools to support reporting and decision-making. Mentor junior team members while fostering a culture of excellence in data and analytics, positioning the team as a hub of expertise and innovation
Minimum Qualifications
8+ years work experience in increasingly senior analytical roles in technology and finance industry
Strong background in payments, product, or operations analytics, with hands-on proficient in SQL, Python and/or R
Exceptional track record of deriving actionable insights from analysis and analytical storytelling
Experience working with large datasets, unstructured data, data modeling, and data pipelin ... (truncated, view full listing at source)
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