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Daloopa is seeking a seasoned Product Manager to own the Scout product, an AI-native analyst workflow tool. You will shape strategy, define end-to-end workflows, and work closely with engineering and design to deliver features that improve analyst efficiency and decision quality.
Ideal candidates bring 5+ years in product management, proven experience shipping AI-driven products, and a track record of influencing roadmap decisions in fast-paced startups.
Daloopa is transforming how investment professionals work. Our mission is to eliminate the slow, error-prone parts of fundamental research, without sacrificing accuracy or auditability.
Founded by a former equity research analyst and top engineers, we built an AI-powered platform that converts complex financial filings, transcripts, and KPIs into clean, hyperlinked, customizable data. This means analysts spend less time on manual tasks and more time generating insights that drive performance.
Today, Daloopa powers the workflows of leading investment teams worldwide helping them move faster, think deeper, and make every decision with confidence. If you’re passionate about building technology that solves real-world problems and want to make an impact, join us and help redefine the future of investment research.
Location: New York City (Hybrid office/remote schedule)
Compensation: $205,000 - $225,000base salary+equity +benefits(This range is reflective of level of contribution. Candidates who fully match whatwe’relooking for in this role will be at the top of therange.)
Scout isDaloopa'sAI-native product for the analyst workflow: not a prompt tool, not a chatbot, but an agent that understands what analysts are doing and works alongside them. As the PM for Scout, you own the product from strategy through execution.That means deciding what gets built, why it gets built, and making sure it actually changes how analysts work.This is not a coordination role. You will have real ownership, real accountability, and the room to make calls that shape one of the company’s biggest product bets.
Theproblemspace is challenging. Financial analysts are expert users with low tolerance for noise andhigh expectationsfor accuracy. Building AI products in that context requires understanding both the workflow and the technology well enough to make honest tradeoffs. You need to know when AI is the right answer and when it is not. If you have shipped AI products that changed user behavior, stayed close to the technical work, and are ready to do that again at a company that is still early enough for your decisions to matter, this is your seat.
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