Head of Data

Responsibilities

• Decision science. Own attribution, incrementality, LTV / CAC, customer segmentation, forecasting, and experimentation across our business units. Set the methodologies, defend them, and improve them as we learn.
• Flywheel measurement. Build the analytical view of how our businesses (admin, Carry, Ark, Meridian) reinforce each other, where the flywheel is real, where it’s aspirational, and what investments accelerate it.
• Experimentation. Make running good experiments the default for product, marketing, and growth, with the infrastructure and review process to back it up.
• The data platform. Inherit a working platform with real gaps. Decide which gaps to fill, which to accept, and how to keep investing so the foundation grows with the demands you’re putting on it.
• The team. Three people today, a mix of data engineering and analytics. Grow it deliberately. We expect early hires to be data scientists who reflect the bar you set, not headcount for its own sake.
• Executive partnership. Be a thought partner to the CFO, CEO, and the GMs, in the room for capital allocation and GTM decisions, not summarizing them afterward.

Requirements

• 8+ years in data science, decision science, or growth analytics, including hands-on practitioner work. At least 2 years leading teams.
• Deep expertise in some combination of attribution, causal inference, experimentation, LTV / CAC, segmentation, forecasting, and marketplace measurement.
• Strong Python and SQL. You’ve built models recently enough to still be opinionated about how to build them.
• Track record of changing executive decisions through analysis.
• Exceptional written communication.
• Maturity with the platform layer. You don’t have to be the deepest data engineer in the room, but you have to make good architectural calls and respect the work of the engineers on your team.
• A genuine appetite for being a player-coach.

Nice-to-Haves

• Marketplace, fintech, or financial services background.