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# Senior Manager, Data Science

- **Company:** Upstart
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $182,800.0 - $270,400.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Python (Programming Language), SQL Databases, Information Technology
- **Published:** October 21, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=d5cde11d9059f3e6

## About the Role

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., * 10+ years in data science and analytics, including 5+ years managing teams of analysts and data scientists

 * Technical depth across the work a marketing analytics and data science team does, including reporting, experiments, causal inference, and attribution, and a clear sense of which approach a given question needs
 * Enough SQL and Python to check your team's work yourself
 * A record of hiring well and growing people into more senior roles
 * Good judgment in ambiguous, greenfield areas: you can frame a question nobody has asked yet and decide whether it's worth the team's time
 * Clear written and verbal communication with marketing, finance, product, and technical audiences, and the willingness to tell a senior leader when the evidence doesn't support their plan, * An exceptional candidate will also have:
 + A PhD or master's degree in statistics, economics, computer science, or another quantitative field
 + Experience bringing AI tools into a team's analysis and reporting work

## Description

Marketing Science sits within Upstart's Growth, Product, and Ops Analytics team and answers two questions for the business: is our marketing working, and where should it go next? The team's analysts and data scientists are embedded with growth marketing across every channel that brings borrowers to Upstart, including direct mail, paid search and social, video, mobile, email, brand campaigns, and lending partnerships. Within a channel, they work out what's performing and how to make it better. Across channels, they look at how spend should be divided and how each channel affects the others., * Lead a team of analysts and data scientists who are embedded with each marketing channel and responsible end to end for its work

 * Put experimentation at the center of the team's work: decide which tests are worth running across channels, and make sure the results change what marketing does next
 * Guide the team's analysis toward explaining why a channel's performance moved and what marketing should do about it
 * Push the team to bring forward work nobody asked for, like analysis that spots a problem or an opportunity, before marketing knows to ask
 * Hold a high bar on the team's measurement work, including incrementality tests and attribution, and ensure high-quality outputs
 * Work with marketing, finance, and product leaders to set the team's roadmap, and bring that business context back so your team works on the right problems
 * Hire and develop a team that marketing leaders treat as a partner, not a reporting servic