Senior Manager of Data Science, Upstart

• 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

Desirable

• 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
• At Upstart, a marketing dollar only pays off if it reaches someone our AI models approve and who then takes the loan, so the team's questions go well past the click. And since we see the full path from first touch to funded loan, the team can measure marketing against that outcome rather than a stand-in for it
• You'll lead that team and work directly with Upstart's marketing leaders, acting as a thought partner to optimize for what is best for the company. We're looking for an experienced data science and analytics leader who can raise the impact this team has on Upstart's growth
• 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