ironquill.tech/board

$ cat jobs/vp-data-updater-32d2a1dfc51c.json

VP, Data

updater·US·United States·mid
mlllm
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View All Jobs Updater operates at the intersection of affiliate marketing, embedded commerce, and consumer marketplaces where we create (and lose) revenue through complex, multi-party data flows. In this environment, data isn’t a support function—data runs the business. We’re seeking a VP of Data to materially elevate how we make data-driven decisions across the company. Reporting to the SVP of Engineering, this leader will architect the systems, standards, and team that transform fragmented signals into trusted, decision-enabling intelligence. This business-critical leadership role will directly impact growth, margin, risk mitigation, and executive velocity. You will build the canonical data engine powering a complex B2B2C marketplace—increasing trust, speed, and profitability through better systems and sharper insight. We’re also aggressively leaning into machine learning and AI. We’ve been developing LLM-based agentic models to help consumers purchase complex products with confidence. In addition the engineering and data teams have been utilizing Claude Code, Codex, and other LLM-based tools to increase insights and productivity. We believe strongly in being a thought leader in this space. If you’re motivated by meaningful ownership and the chance to turn complexity into competitive advantage, this role offers a rare opportunity to do exactly that. What Success Looks Like Stakeholders trust the numbers—even when they’re uncomfortable Revenue questions that once took weeks now take hours or minutes Leading indicators surface risk before it hits the P&L KPIs are clearly defined, role-aware, and consistently interpreted Data enables faster, smarter decision-making across the company External data anomalies get identified immediately, rather than weeks later Clearly defined schema, data usage rules, and organizational understanding both in a financial and product landscape. Data can be consumed by humans and AI models with the correct semantic boundaries. Key Respons

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