HappyRobot provides a vertical AI agent platform that automates logistics, freight, and customer-support workflows across phone, email, chat, OCR, browser automation and integrates with TMS, ERP, and CRM.
ABOUT HAPPYROBOT HappyRobot is the infrastructure for enterprises to build and orchestrate AI workforces. Our AI workers don't just communicate - they make decisions, take action, and run operations autonomously across voice, email, and enterprise systems. Born in Y Combinator (S23) and backed by a16z and Base10 with over $60M raised, we power critical operations for global enterprises worldwide. Our platform is battle-tested in the most demanding environments - where AI has real consequences. We started in logistics, built our own voice stack, models, and orchestration layer from the ground up, and are now bringing that infrastructure to every enterprise that runs the real economy. Learn more about our vision in our manifesto. https://www.happyrobot.ai/blog/manifesto ABOUT THE ROLE You’ll help make data a core part of how we build and improve HappyRobot’s products. You’ll work closely with Product, Engineering, and Machine Learning teams to measure how changes to our models, agents, and product features affect real-world performance. You’ll define meaningful metrics, design experiments, and conduct deeper analyses to understand how our agents create value for clients. Your work will range from evaluating A/B tests and model changes to analyzing millions of conversations and workflows. You’ll turn complex data into clear insights that influence our product and ML roadmaps. WHAT YOU’LL DO - Define and track product, feature, and agent-level metrics. - Design, run, and interpret A/B tests for model changes, prompts, agent behavior, workflows, and product features. - Measure how the performance of our agents affects client outcomes, such as task completion, operational efficiency, response quality, and automation rates. - Connect offline model evaluations with production performance and real-world customer impact. - Conduct deep analyses across conversations, workflows, and product usage to identify opportunities and explain differences in performance. - Investigate anomalies and regressions, perform root-cause analyses, and recommend improvements. - Build statistical models, simulations, and analytical frameworks to support product and ML decisions. - Partner with Engineering to improve instrumentation, data quality, experimentation systems, and analytical data models. - Build dashboards and self-serve tools that help teams understand product and agent performance. - Communicate findings and recommendations clearly to technical and non-technical stakeholders. MUST HAVE - 4+ years of experience in Data Science, Product Analytics, or another highly quantitative product role. - Strong experience with experimental design, A/B testing, statistics, causal inference, and hypothesis-driven analysis. - Advanced proficiency in SQL and Python. - Experience defining and operationalizing product and feature metrics. - Ability to translate ambiguous product questions into rigorous analyses and actionable recommendations. - Strong product instincts and the ability to distinguish statistical significance from meaningful product or customer impact. - Experience partnering closely with Product, Engineering, or Machine Learning teams. - Strong written and verbal communication skills. - High attention to detail and commitment to analytical accuracy. - Founder mindset: ownership, independence, curiosity, and willingness to go deep. NICE TO HAVE - Experience working with large language models, AI agents, generative AI, or other probabilistic ML products. - Experience measuring the production impact of model, prompt, retrieval, or orchestration changes. - Familiarity with ML evaluation systems and the relationship between offline evaluations and online metrics. - Experience analyzing conversational, NLP, speech, or other unstructured data. - Experience with enterprise or B2B products. - Experience combining quantitative analysis with qualitative methods such as conversation reviews, customer feedback, surveys, or user research. - Familiarity with modern analytics infrastructure, data warehouses, experimentation platforms, and business intelligence tools. - Prior experience in a fast-growing startup or other highly ambiguous environment. WHY JOIN US? - Opportunity to work at a high-growth AI startup, backed by top investors. - Rapidly growing and backed by top investors including a16z, Y Combinator, and Base10. - Ownership & Autonomy - Take full ownership of projects and ship fast. - Top-Tier Compensation - Competitive salary + equity in a high-growth startup. - Comprehensive Benefits - Healthcare, dental, vision coverage. - Work With the Best - Join a world-class team of engineers and builders Our Operating Principles Extreme Ownership We take full responsibility for our work, outcomes, and team success. No excuses, no blame-shifting — if something needs fixing, we own it and make it better. This means stepping up, even when it’s not “your job.” If a ball is dropped, we pick it up. If a customer is unhappy, we fix it. If a process is broken, we redesign it. We don’t wait for someone else to solve it — we lead with accountability and expect the same from those around us. Craftsmanship Putting care and intention into every task, striving for excellence, and taking deep ownership of the quality and outcome of your work. Craftsmanship means never settling for “just fine.” We sweat the details because details compound. Whether it’s a product feature, an internal doc, or a sales call — we treat it as a reflection of our standards. We aim to deliver jaw-dropping customer experiences by being curious, meticulous, and proud of what we build — even when nobody’s watching. We are “majos” Be friendly & have fun with your coworkers. Always be genuine & honest, but kind. “Majo” is our way of saying: be a good human. Be approachable, helpful, and warm. We’re building something ambitious, and