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Jerry.ai is a fast-growing fintech/insurtech platform that has scaled to 5M+ customers and $240M+ in funding. The company started with car insurance in 2019, became a top-3 US broker, and has since expanded into driving insights, diagnostics, repair marketplaces, and adjacent verticals (home, motorcycle, RV). The company reached profitability in early 2024 and is targeting 50M customers and $10B valuation within 4 years.
The BizOps & Analytics team is composed of former McKinsey, BCG, and Bain consultants who drive data-informed decision-making across product, growth, tech, and operations. Each business unit has an embedded BizOps analyst. The company is hiring 4-6 people across Growth Marketing, Product Development, AI & Automation, and Strategic Partnerships.
As Manager, you will lead the analytical function for one of Jerry's core business areas (growth, product, AI/automation, or strategic partnerships). You'll own the full analytical lifecycle: defining the right business questions, building metrics and reports, running analyses and experiments, and driving recommendations through to execution. You'll sit on the central BizOps team but be embedded within your assigned business unit, acting as a first-principles problem solver who shapes what questions to ask, what data to pull, and what decisions to make.
Key responsibilities include: defining metrics and KPIs for your domain, building dashboards and reports in Metabase, running SQL/Python analyses, designing experiments, surfacing insights, and presenting findings to leadership to drive decisions. You'll be hands-on—this is not a pure strategy role. You'll also own execution and see initiatives through end-to-end.
The culture emphasizes impact over process: no slide decks, no corporate bloat, no unnecessary meetings. Every person owns a critical domain. You'll work with a team of 14 analytical professionals who are insatiable learners focused on solving difficult problems.
Required: 4+ years at a consulting firm, investment bank, or high-growth tech company. Strong SQL/Python skills, ability to pull and interpret data independently, track record of owning ambiguous problems and delivering measurable impact, and clear communication skills to influence leadership-level decisions.
