AI Analyst - Business Analytics and Product Intelligence

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.

• →Own subscription and product analytics end-to-end: conversion funnels, cohort retention, churn analysis, LTV modeling, and revenue tracking
• →Build and maintain production dashboards and alerting systems that the team relies on daily for business-critical metrics
• →Conduct deep exploratory analysis on user behavior, identifying engagement patterns, diagnosing drop-offs, and quantifying the impact of product and pricing changes
• →Write highly optimized SQL against a modern data stack (BigQuery, PostgreSQL), including complex CTEs, window functions, and cross-database joins
• →Maintain and evolve the company's analytics knowledge base, documenting schemas, metric definitions, and known data quality issues so the team can self-serve
• →Partner with product and engineering to define experiments, validate A/B tests, and ensure proper attribution across channels
• →Use AI tooling (Claude, MCP servers, agentic pipelines) to automate data exploration, query generation, anomaly detection, and reporting, treating AI as a core part of your workflow, not an afterthought

• 5+ years of strong SQL proficiency, you think in CTEs and window functions, you understand partitioning tradeoffs, and you instinctively validate results against multiple sources before drawing conclusions
• Experience with subscription/SaaS metrics: MRR, churn, cohort analysis, conversion funnels, and usage-based billing
• A hypothesis-driven mindset, you don't just pull numbers, you form a thesis, test it iteratively, and revise when the data disagrees
• Comfort with messy, evolving data infrastructure, you can navigate pipeline delays, schema inconsistencies, and incomplete data without getting stuck
• Familiarity with product analytics tools (PostHog, Mixpanel, Amplitude, or similar) and concepts like identity stitching and multi-touch attribution
• Experience building dashboards and visualizations that non-technical stakeholders actually use
• Eagerness to use AI assistants and agentic tools as part of your daily workflow, automating boilerplate, generating initial analyses, and iterating faster than a purely manual approach allows
• Strong async communication skills, you can document findings, flag issues, and propose next steps clearly enough that teammates can act without a follow-up meeting

• Experience with BigQuery, Redash, or similar BI tooling
• Familiarity with Python or dbt for data transformation
• Exposure to event-driven data models and behavioral analytics
• Comfort working directly with engineering teams on data pipeline issues
• Prior work at an early-stage startup where you built the analytics layer from scratch