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Confidencial

Madrid

Data Scientist, Applied Science

PresencialMidFull-time

Publicado 25 de junio de 2026 · 1 visualizaciones

Oferta externa

Esta vacante proviene de una fuente externa. La descripción puede estar abreviada y algunos datos (salario, habilidades) pueden no estar disponibles. Regístrate como candidato para recibir la información completa.

Descripción del puesto

Do you want to drive the next urban revolution? At Cabify, that’s what we’re doing. We aim to make cities better places to live by improving mobility for the people living in them, connecting riders to drivers at the touch of a button. Maybe one day cities will be places where nobody needs a private car. But we’ve still got a long way to go… want to be part of this journey? About the position You will join Cabify’s Applied Science team, a group of highly motivated data scientists with access to all data within the organization. The team is involved in all main areas of the company, including vehicle and route management, understanding user experience, pricing, fraud detection, and marketing optimization (see for yourself: exhibit A , exhibit B , exhibit C ). You will work with state-of-the-art tools and infrastructure to help improve everyday operations in more than 40 cities worldwide. Cabify's Applied Science team provides a unique opportunity to research, test and implement great ideas that will shape the future of our cities. As a Data Scientist in our team, you will: Develop high-impact data science projects, working closely with other data, engineering, product and business teams. Design, train, and validate statistical and machine learning models and help deploying them into production. Participate in the results analysis of real-life experiments, following academy-standard scientific methods and procedures, to demonstrate the impact of the new product features we develop. Help to convert the team’s technical knowledge into real and tangible business insights that bring value to the company. Join product development conversations, discussing new features and bringing the data science perspective to everything we build. What we’re looking for At least 3 years of professional experience working as a data scientist or equivalent research role. Strong educational background, e.g Masters in Computer Science, Physics, Engineering, Mathematics, Economics, etc. Solid foundations in Probability Statistics. Experience designing, training and validating statistical and machine learning models. Experience working with Python for data analysis and data visualization libraries. Experience with data extraction and processing. Capable of writing complex SQL code. Ability to work autonomously in an unstructured environment. Bonus Points Experience bringing machine learning to production, with all its subtleties: deploying, training, testing, model degradation, model serving, etc. Experience with state-of-the-art methods in topics like deep learning models, time series analysis, bayesian statistics, causal inference, etc. Experience with geo data modeling, analysis and visualization. What’s it like to work at Cabify? We’re a company full of happy, motivated people and we never want that to change. Here are some more reasons why it rocks to be part of our high-performance team: 💶 Excellent Salary conditions: 38K - 53K€ 🏝️ Recharge days! (10 Free Fridays annually) 🌍 Our office is located in Madrid. ⌚ Flexible work environment hours. 🙌 Regular team events. 🚗 Cabify staff free rides. 🚀 Personal development programs based on our career paths. 📐 Coursera: your own license in Coursera to take as many courses as you wish and continue developing your skills. 🧘‍♀️ iFeel: Free access to the iFeel platform, so you can take care of your emotional well-being through therapy sessions. 💳 Flexible compensation plan: Restaurant tickets, transport tickets, healthcare and childcare 🐱 A pet room ,so you don’t have to leave your furry friend at home ☕️ And last but not least...free coffee and fruit! Cabify is proud of being an equal opportunity workplace. We celebrate diversity and we are committed to creating an inclusive environment for all employees regardless of background, gender, religion, orientation, age or ability. Join us!

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