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, and fundraising narratives Build production dashboards, ML-powered alerting systems, and forecasting tools that leadership relies on daily, and evolve the knowledge base so teams can self-serve Champion AI-native data science: deploy Claude, MCP servers, and agentic workflows to automate exploration, feature engineering, anomaly detection, query generation, and reporting at scale Act as the trusted data and modeling partner to the CEO and functional leaders, translating complex analysis and models into clear, decision-ready recommendations Who You Are: 12+ years in data science, analytics, or a related quantitative field, with 5+ years leading and scaling data science and analytics teams at high-growth B2C/SaaS or PLG companies Deep expertise in subscription and SaaS metrics: MRR, churn, cohort analysis, LTV modeling, conversion funnels, and usage-based billing Strong foundation in statistical modeling and applied machine learning: regression, classification, time-series forecasting, and propensity/uplift modeling, with the judgment to know when a simple model beats a complex one Elite SQL proficiency: you think in CTEs and window functions, understand partitioning tradeoffs, and validate results against multiple sources instinctively Proven track record of building data science and analytics functions from scratch or through hypergrowth: hiring, tooling, metric and model governance, and stakeholder trust Strong command of the modern data stack: BigQuery or similar warehouses, dbt, product analytics tools (PostHog, Mixpanel, Amplitude), and BI platforms Experimentation depth: you've designed and governed A/B testing programs and understand statistical rigor, causal inference, identity stitching, and multi-touch attribution A hypothesis-driven operator: you form a thesis, test it iteratively, build models to validate it, and revise when the data disagrees, and you've taught teams to do the same Genuine conviction in AI-native workflows: you use AI assistants and agentic tools daily and have strong opinions on how they transform data science and analytics work Executive-grade communication: you can walk into a board meeting or a leadership review and land a data-backed recommendation in five minutes Comfort with ambiguity and messy, evolving data infrastructure: you unblock yourself and your team without waiting for perfect pipelines Nice to Have: Experience at a developer tools, AI, or vibe coding platform Strong Python fluency for statistical modeling, ML, and automation (pandas, scikit-learn, statsmodels, or similar) Prior ownership of finance-adjacent analytics: revenue recognition, forecasting, and unit economics for board reporting Experience partnering directly with engineering on event-driven data models and behavioral analytics Experience deploying models into production (not just notebooks), with MLOps fundamentals a plus Early-stage startup experience where you built the data science and analytics layer from zero to scale Benefits and Perks: Daily Meals: Lunch and Dinner provided Family Insurance: 5 Lakhs worth of coverage for you and your family Unlimited Paid Time Off: Take the time you need to recharge and come back refreshed Flexible Working Hours: Work arrangements that fit your life and commitments Let's build the future of software together.