Sobre

• About Nubank
• Nubank was founded in 2013 to free people from a bureaucratic, slow and inefficient financial system. Since then, through innovative technology and outstanding customer service, the company has been redefining people's relationships with money across Latin America. With operations in Brazil, Mexico, and Colombia, Nubank is today one of the largest digital banking platforms and technology-leading companies in the world.
• Today, Nubank is a global company, with offices in São Paulo (Brazil), Mexico City (Mexico), Buenos Aires (Argentina), Bogotá (Colombia), Durham (United States), and Berlin (Germany). It was founded in 2013 in Sao Paulo, by Colombian David Vélez, and cofounded by Brazilian Cristina Junqueira and American Edward Wible. For more information, visit www.nu.com.mx.
• Machine Learning Engineering at Nubank
• Data Science is essential to every part of the business at Nubank, since Day 1. Most areas of the company use data science to some extent. ML Engineers are key to connecting ML models and ML-enabled systems to the rest of our infrastructure, while making sure that they work properly, delivering value to our customers.

As a Machine Learning Manager, you’re expected to

• As a ML Manager, you will have the opportunity to partner with the rest of Nubank to help us innovate with machine learning to optimize the decisions we make and simplify the lives of our millions of customers. With your help, we will build the most defining financial technology company in the world, creating an immense impact for millions of customers. We will disrupt this market and bring competition and efficiency to an industry that urgently needs it.
• ML Managers at Nubank are responsible for developing and growing high-performing teams of data scientists and ML engineers.
• Lead by defining the vision of the team and help the team deliver on the vision by setting clear goals and objectives, providing information and context, clearing obstacles, brokering consensus, and working quickly to close gaps in key resources and skills.
• Attend to the team and individual health and performance by safeguarding the team’s psychological safety, providing clear, specific, timely feedback, taking decisive actions to manage performance, advocating for recognition of the contributions of the team, and protecting the team from unproductive pursuits.
• Conduct performance reviews, participate in calibration, solicit feedback, and generally perform the administrative functions of people management.
• What are we looking for?
• ML Managers will generally have strong technical backgrounds in disciplines related to data science and ML since they need to be able to assess technical performance, manage resourcing plans, provide coaching and help their team members grow professionally. However, frequently, their team members may have quite different technical skills and they may work in other squads and tribes. In such cases, ML Managers will have to ensure that they actively solicit input and feedback from experts who share the same technical backgrounds as their reports and from managers and leaders who can assess their performance.
• Has experience creating, deploying and maintaining ML models and ML-enabled systems using modern frameworks;
• Is familiar with cloud-based services from vendors such as AWS, GCP, Azure, etc;
• Is familiar with software engineering and architecture principles and how they enable sustainable and maintainable systems;
• Is familiar with data engineering routines, pipelines and job scheduling frameworks;
• Since much of data science shares work patterns with engineering and software development, ML managers should have a good understanding of the software development lifecycle and the popular tools used in modern systems. They should also understand, at a conceptual level, the specific concerns of the data science modeling life cycle including the steps of data preparation, model training, model management, logging, and monitoring of models in production. Both these dimensions of knowledge will be necessary to manage effectively in this role.
• ML Managers must also be excellent problem solvers, adept at working across teams of engineers, analysts, product managers, and business leaders in order to address conflict, drive consensus, and make decisions in the best interests of the company. They must be able to help their teams prioritize their work, make smart, timely decisions, and execute at a high level of professional skill, quality, and speed.
• Our Benefits
• Chance of earning equity at Nubank
• Food/ Meal Card (Vale-Refeição and/or Vale Alimentação)
• Public Transportation Commuting Benefit (Vale-Transporte)
• NuCare – Psychological, Financial and Legal Assistance Program
• Life Insurance
• Medical Plan
• Dental Plan
• NuLanguage – Language Course Program
• Nucleo - Our learning platform of courses
• Extended Parental Leave
• Daycare Allowance
• Parental Consultancy
• Work-from-home Allowance
• Gym Partnerships
• 30 days of paid vacation
• Relocation Assistance Package, if applicable
• Work Model for this Role
• Hybrid 2-3 times/week: Our hybrid work model brings us to the office at least twice a week, on strategic days designed to maximize team connection and collaboration. For more details, visit https://building.nubank.com/nu-hybrid-work-model/
• Role Location
• São Paulo - Brasil