Head of Data

Why Join AngelList

We’re solving some of the hardest problems in venture capital and private markets. You’ll work with a team that values precision, urgency, and long-term thinking. If you want to shape how startups are funded and built, this is the place. About AngelList We exist to accelerate innovation by increasing the number of successful startups in the world. We do this by building the financial infrastructure that makes it easier for more people to invest in world-changing companies. AngelList is the nexus of venture capital and the startup community. We support $171B+ in assets and have powered investments into over 13,000 startups—over 300 of which are unicorns. Today, 57% of top-tier U.S. VC deals involve investors on AngelList. While our scale is large, our ambition is larger. If you're excited to build the future of private markets, come build with us.

About the Role

We're hiring a Head of Data to turn AngelList's data into an unfair advantage. AngelList sits in a rare position. We support $171B in assets across 25,000+ funds and syndicates, with $80B+ moved across our banking infrastructure. 80% of the top 10 2025 Midas List VCs invest in funds on AngelList. Our network spans 2,300+ GPs and 72,000+ LPs, the largest in private markets, and we have over a decade of venture fund transaction data underneath it. We've reached $100M+ ARR with essentially zero marketing spend and we're ready to invest. The business is unusual: a marketplace, an investing platform, a banking partner, and a software + services business, all reinforcing each other. The data implications are extraordinary, and most of the interesting questions are still unanswered. Those questions are the work. How do the business units actually compound on each other? What's the right attribution model when one product introduces a customer to another? What does incrementality look like when our channels are dominated by network and reputation rather than paid acquisition? What's the LTV of a fund manager vs. an LP vs. a banking customer, and how should that change where we invest? Our data team spent the last year earning trust in the numbers: Snowflake live, pipelines reliable, a shared source of truth. That foundation is mostly there. What we want next is the layer on top: attribution we trust, incrementality we can measure, segmentations and forecasts that change how we invest, experimentation as default. You'll lead a small, senior team of three to start, and personally do a meaningful share of the work and shaping of the team. For a growth-focused data scientist ready to do both, there aren't many roles like it.