Role description
Data Analytics Lead
HappyRobotAbout HappyRobot
HappyRobot is the infrastructure for enterprises to build and orchestrate AI workforces. Our AI workers don't just communicate through voice and email - they make decisions, take action, and run operations autonomously across entire enterprise systems. Born in Y Combinator (S23) and backed by a16z, Base10, Prysm Capital and Eurazeo with over $200M 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.
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?
Join a world-class team of engineers and builders.
Backed by top investors including a16z, Y Combinator, Base10, Prysm Capital and Eurazeo.
Have ownership and autonomy of projects and are encouraged to ship.
Comprehensive Benefits including healthcare, dental, vision coverage.
Competitive salary + equity in a high-growth startup.
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 it’s easier (and more fun) when we enjoy the ride together. We give feedback with kindness, challenge each other with respect, and celebrate wins together without ego.
Urgency with Focus
Create the highest impact in the shortest amount of time. Move fast, but in the right direction. We operate with speed because time is our most limited resource. But speed without focus is chaos. We prioritize ruthlessly, act decisively, and stay aligned. We aim for high leverage: the biggest results from the simplest, smartest actions. We’re running a high-speed marathon — not a sprint with no strategy.
Talent Density and Meritocracy
Hire only people who can raise the average; ‘exceptional performance is the passing grade.’ Ability trumps seniority. We believe the best teams are built on talent density — every hire should raise the bar. We reward contribution, not titles or tenure. We give ownership to those who earn it, and we all hold each other to a high standard. A-players want to work with other A-players — that’s how we win.
First-Principles Thinking
Strip a problem to physics-level facts, ignore industry dogma, rebuild the solution from scratch. We don’t copy-paste solutions. We go back to basics, ask why things are the way they are, and rebuild from the ground up if needed. This mindset pushes us to innovate, challenge stale assumptions, and move faster than incumbents. It’s how we build what others think is impossible.
The personal data provided in your application and during the selection process will be processed by Happyrobot, Inc., acting as Data Controller.
By sending us your CV, you consent to the processing of your personal data for the purpose of evaluating and selecting you as a candidate for the position. Your personal data will be treated confidentially and will only be used for the recruitment process of the selected job offer.
In relation to the period of conservation of your personal data, these will be eliminated after three months of inactivity in compliance with the GDPR and legislation on the protection of personal data.
If you wish to exercise your rights of access, rectification, deletion, portability or opposition in relation to your personal data, you can do so through security@happyrobot.ai subject to the GDPR.
For more information, visit https://www.happyrobot.ai/privacy-policy
By submitting your request, you confirm that you have read and understood this clause and that you agree to the processing of your personal data as described.