Data Scientist
il y a 3 jours
Barcelona
ph3About HappyRobot /h3 pHappyRobot 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. /p pOur 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. /p h3About the Role /h3 pYou’ll help make data a core part of how we build and improve HappyRobot’s products. /p pYou’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. /p pYour 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. /p h3What You’ll Do /h3 ul liDefine and track product, feature, and agent-level metrics. /li liDesign, run, and interpret A/B tests for model changes, prompts, agent behavior, workflows, and product features. /li liMeasure how the performance of our agents affects client outcomes, such as task completion, operational efficiency, response quality, and automation rates. /li liConnect offline model evaluations with production performance and real-world customer impact. /li liConduct deep analyses across conversations, workflows, and product usage to identify opportunities and explain differences in performance. /li liInvestigate anomalies and regressions, perform root-cause analyses, and recommend improvements. /li liBuild statistical models, simulations, and analytical frameworks to support product and ML decisions. /li liPartner with Engineering to improve instrumentation, data quality, experimentation systems, and analytical data models. /li liBuild dashboards and self-serve tools that help teams understand product and agent performance. /li liCommunicate findings and recommendations clearly to technical and non-technical stakeholders. /li /ul h3Must Have /h3 ul li4+ years of experience in Data Science, Product Analytics, or another highly quantitative product role. /li liStrong experience with experimental design, A/B testing, statistics, causal inference, and hypothesis-driven analysis. /li liAdvanced proficiency in SQL and Python. /li liExperience defining and operationalizing product and feature metrics. /li liAbility to translate ambiguous product questions into rigorous analyses and actionable recommendations. /li liStrong product instincts and the ability to distinguish statistical significance from meaningful product or customer impact. /li liExperience partnering closely with Product, Engineering, or Machine Learning teams. /li liStrong written and verbal communication skills. /li liHigh attention to detail and commitment to analytical accuracy. /li liFounder mindset: ownership, independence, curiosity, and willingness to go deep. /li /ul h3Nice to Have /h3 ul liExperience working with large language models, AI agents, generative AI, or other probabilistic ML products. /li liExperience measuring the production impact of model, prompt, retrieval, or orchestration changes. /li liFamiliarity with ML evaluation systems and the relationship between offline evaluations and online metrics. /li liExperience analyzing conversational, NLP, speech, or other unstructured data. /li liExperience with enterprise or B2B products. /li liExperience combining quantitative analysis with qualitative methods such as conversation reviews, customer feedback, surveys, or user research. /li liFamiliarity with modern analytics infrastructure, data warehouses, experimentation platforms, and business intelligence tools. /li liPrior experience in a fast-growing startup or other highly ambiguous environment. /li /ul h3Why join us? /h3 ul liOpportunity to work at a high-growth AI startup, backed by top investors. /li liRapidly growing and backed by top investors including a16z, Y Combinator, and Base10. /li liOwnership Autonomy - Take full ownership of projects and ship fast. /li liTop-Tier Compensation - Competitive salary + equity in a high-growth startup. /li liComprehensive Benefits - Healthcare, dental, vision coverage. /li liWork With the Best - Join a world-class team of engineers and builders. /li /ul h3Our Operating Principles /h3 pExtreme Ownership /p pCraftsmanship /p pWe 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. /p pUrgency 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. /p pTalent 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. /p pFirst-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. /p pBy 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. /p pIn 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. /p pIf you wish to exercise your rights of access, rectification, deletion, portability or opposition in relation to your personal data, you can do so through subject to the GDPR. /p pFor more information, visit /p pBy 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. /p /p #J-18808-Ljbffr