Join Emergent, a leading AI platform revolutionizing software development. We build autonomous coding agents that generate, test, and deploy applications from simple language inputs. With over $130M ARR and 10M+ users globally, our systems are trusted for production applications at scale. We are backed by top-tier investors and comprised of experienced founders and engineers from leading tech companies.

We seek talented individuals passionate about ownership, speed, and global impact to join our mission. If you're driven to build and innovate, we encourage you to explore this opportunity.

As an Analytics Leader, you will spearhead the entire data and analytics function for one of the world's fastest-scaling AI platforms. Your role involves defining key metrics, establishing measurement frameworks, and ensuring data informs critical decisions across product, growth, finance, and leadership.

You'll act as a player-coach, setting the analytics vision, building and leading a high-performing team, while also diving deep into data to solve complex problems. You will be the primary source for business-critical metrics like revenue, retention, and unit economics. This is an AI-native leadership role, integrating AI tools as core infrastructure for maximum team efficiency.

We are looking for a seasoned professional with 12+ years in data science or analytics, including at least 5 years of leadership experience in high-growth B2C/SaaS or PLG environments. A deep understanding of subscription and SaaS metrics is essential.

Your expertise should encompass statistical modeling, applied machine learning, and elite SQL proficiency. You should have a proven history of building data science and analytics functions from the ground up. Familiarity with modern data stacks, experimentation design, and a hypothesis-driven approach are key.

Genuine conviction in AI-native workflows and executive-grade communication skills are crucial. Comfort with ambiguity and evolving data infrastructure is also expected. Nice-to-have qualifications include experience in developer tools or AI platforms, strong Python fluency, and prior ownership of finance-adjacent analytics.