Analytics & Data Science Leader

Emergent builds autonomous coding agents that replace traditional software development by generating, testing, and deploying production applications directly from plain-language intent. Our systems run in production at global scale and are used to build millions of real applications. Since our public launch, we've crossed $130M in Annualised Revenue and grown to over 10M users across 190+ countries , who have built 12M+ applications on Emergent. We're backed by Creaegis, Khosla Ventures, SoftBank, Lightspeed, Together, Y Combinator, Google, Claypond and Sentinel Global. We're solving the hard part of AI-driven software creation: correctness, reliability, security, and scale in real production systems. The team is built by repeat founders, Olympiad medalists, IIT & IIM alumni, and leaders from Google, Amazon, and Dropbox. We're hiring builders who want ownership, speed, and impact at global scale. The Role: We're looking for an Analytics Leader to own the entire data and analytics function at one of the fastest-scaling AI platforms in the world. You'll define what we measure, how we measure it, and how data drives every major decision across product, growth, finance, and leadership. This is a player-coach role. You'll set the analytics vision, build and lead a high-performing team, and still stay close enough to the data to pressure-test a pricing model or debug an attribution issue yourself. You'll report directly to leadership and act as the single source of truth for business-critical metrics: revenue, retention, conversion, and unit economics. Critically, this is an AI-native analytics leadership role. You'll build a function where AI tools (Claude, MCP integrations, agentic pipelines) are core infrastructure, not add-ons, enabling a lean team to deliver the output of one many times its size. What You'll Do: Own the company-wide data science and analytics strategy: define the metrics framework, predictive models, north-star KPIs, and reporting cadence used by leadership, product, growth, and finance Build, hire, and lead the data science and analytics team, setting the bar for rigor, speed, and self-serve enablement across the company Own subscription and revenue analytics end-to-end: MRR, churn, cohort retention, LTV/CAC, conversion funnels, and usage-based billing models Lead applied data science initiatives: churn and LTV prediction, propensity and conversion models, forecasting, anomaly detection, and segmentation to drive product and growth decisions Architect and govern the modern data stack (BigQuery, PostgreSQL, event pipelines), partnering with engineering on data quality, schema design, and pipeline reliability Establish experimentation as a discipline: design the A/B testing framework, define statistical standards and causal inference methods, and ensure proper attribution across channels Deliver strategic analysis and modeling for high-stakes decisions: pricing changes, market expansion, product bets,…