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.

 

Data Science at Nubank

At Nubank we aim to empower our customers to take control of their financial lives. The Data Science team develops models and leverages its expertise to provide the best experience and products, using statistics, Artificial Intelligence, and lots of creativity to predict our customers' behaviors. Our team strives for cutting edge model development techniques, from Machine Learning to Reinforcement Learning and beyond. We're partnering with business and technology to make the speed of thought decisions possible.

 

As a Data Science Manager, you’re expected to:

As a Data Science 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.

• Data Science 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.
• As part of a business unit, DS Managers are able to translate the business needs, define roadmaps, and lead projects composed by cross-functional teams to deliver results.

 

What are we looking for?

• Data Science Managers will generally have strong technical backgrounds in disciplines related to data science 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, DS 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.
  
  
• Since much of data science shares work patterns with engineering and software development, DS 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.
  
  
• Data Science 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.

 

Core Benefits

• Chance of earning equity at Nubank
• Extended maternity and paternity leaves
• Health and life insurance
• NuCare - Our mental health and wellness assistance program
• Nucleo - Our learning platform of courses
• NuLanguage - Our language learning program
• Vacations of 17 workdays
• Gym partnership

Role Location

Mexico City, MX

Our Nu Way of Working

Our work model is hybrid and has cycles that can be from two to three months according to the business of expertise. For every eight or twelve weeks of remote work, one will be at the office.

Diversity & Inclusion

At Nubank, we want to be sure that we're building a more diverse and inclusive workplace that reflects the customers we serve and seek to empower. That's why we hire based on equality. We consider gender, ethnicity, race, religion, sexual orientation, and other identity markers as enriching elements to our company while ensuring neither of them represent a barrier when recruiting fantastic talent.