Finance Manager - FP&A & Controlling

What We're Looking For Experience and background: 5-7 years in Finance, with a clear arc from accounting-trained foundations toward FP&A and finance Exposure to both close/controlling work and forward-looking planning - you have done both and value both AI/SaaS company background is a plus - you understand ARR, churn, CAC, and why revenue recognition in software is not trivial Experience in a scaling environment where processes did not exist yet and you had to build them Technical skills: Strong financial modeling: you build from scratch, not from templates Data-literate: comfortable with SQL or willing to learn, experienced with Data & BI tools (Metabase, Snowflake, or equivalent) Architecture-minded: When you build a model, a reporting structure, or a process, you ask "will this still work at 3x the complexity?" Data flows, model logic, and reporting hierarchies should feel like systems design decisions. Mindset: Automation-obsessed: your default reaction to a recurring task is "how do I make this run itself" Builder mentality: energized by the blank page, not intimidated by it Communication: you can explain a P&L variance to a non-Finance person and knows what they need to see versus what stays in the model Business enabler: You see Finance as a function that makes the business move faster and smarter - not one that slows it down with process for process's sake. You earn trust with business leaders by being the person who shows up with options, while never losing sight of the controls and rigor that protect the company long-term Intellectual curiosity about AI: you don't need to be a technologist or an engineer, but you need genuine interest

Why Join Build from scratch: the Finance function at Dust is being designed now. Your fingerprints will be on the architecture for years. AI-first by default: you will use and shape the product you work for, every day. Scale trajectory: Dust is growing fast. This role grows with it, both in scope and seniority. Location We're prioritizing building our team with an in-person culture at our offices in Paris and San Francisco, because we value the magic that happens when talented people work closely together. Why Dust The models are powerful enough. What's missing is the product layer where AI meets how companies actually work. That's what we're building: the infrastructure that lets any team turn scattered knowledge and tools into coordinated execution with agents they build, own, and run themselves. We use Dust ourselves every day. We get to shape how humans and agents collaborate while solving our own problems with the product we ship. That loop is rare, and it's why we move fast. If you're excited about defining a new category and want to join a determined team of optimists who focus on users, ship fast, and don't take themselves too seriously, we'd love to talk. Even if you don't check every box in our

requirements, we encourage you to apply. We value diverse perspectives and backgrounds, and we're more interested in your potential and passion than a perfect match to our checklist. Learn how we think and work. Our product constitution, a story about our mission Agents at work - Latent Space , podcast with our cofounder, Stanislas Polu, 2024 LLMs reasoning and agentic capabilities over time - dotAI, podcast with our cofounder, Stanislas Polu, 2024

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