About Nubank

Tackling the complex banking system to empower people in one of the most bureaucratic markets in the world seems like a crazy idea, right? But that's why, how, and where Nubank was born. We fight complexity through our transparent and straightforward products and experiences: a no-fee credit card, a rewards program, a lending platform, and a digital savings account. In a nutshell, we are the most innovative tech company in Latin America, and we are obsessed with building financial services and products that make our customers love us fanatically. With over 30 million customers and $820 million raised in investment rounds, we are the fastest growing digital bank in the world, with offices in Brazil, Colombia, Germany, Mexico, and Argentina. And it's still only Day One for us!

Our Data Science Team

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.

Principles

As a chapter, we identified a set of principles that guide behaviors we admire in each other and we pursue as a team:

  • Diverse ensembles don't overfit;
  • We reinforce each other's learning;
  • Mind the person behind the data point;
  • We share the same objective function;
  • We trust our confidence interval;
  • Pursue global maxima.

 

We are looking for an inspiring lead to join our Data Science team in a manager position. In this position, 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.

Responsibilities

The Data Science Manager is responsible for developing and growing high-performing teams of data scientists and ML engineers. They 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. They 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. They conduct performance reviews, participate in calibration, solicit feedback, and generally perform the administrative functions of people management. As part of a business unit, they are able to translate the business needs, define roadmaps, and lead projects composed by cross-functional teams. Finally, they deliver results.

Skills

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, AI 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, AI 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 lifecycle 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.

AI 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, execute at a high level of professional skill, quality, and speed.

Achievements

Data Science managers should have a strong record of growing and managing teams of data scientists and engineers with a track record of delivering high impact solutions to business problems. Evidence includes demonstrated value, quality, and innovation.

Data Science should have a track record of growing and nurturing data science talent and leadership, and teams with cultures characterized by high trust, teamwork, safety, and productivity. 

Once here, you will:

  • Manage a group of Data Scientists and Machine Learning engineers;
  • Be part of a squad, contributing to it by leading projects, performing discovery, supporting roadmap decisions;
  • Review technical work regarding your expertise;
  • Review and join approval processes for Machine Learning models;
  • Work on the requirements of Machine Learning models;
  • Involve in horizontal projects which involve the entire Data Science team, such as career
  • Bring expertise to the team to help design and prioritize projects across the many areas involved in building machine learning products (training, deployment, data consistency, monitoring, governance, etc.);
  • Translate complex business challenges into specific and well-designed machine learning solutions that meet business requirements;
  • Provide technical guidance for more junior team members;
  • Ensure the team maintains a high level of technical excellence;
  • Continuously strive to improve the way we work and organize.

Things you'll need to thrive in this role:

  • Consistent coding skills in any language and autonomy with programming. Python/Scala is a plus;
  • People management skills;
  • Nice data handling skills;
  • Strong analytical skills, good business sense to connect data to decision making;
  • Strong understanding of Machine Learning models development and deployment pipeline;
  • Project management experience;
  • Experience with machine learning tools and libraries such as Scikit-learn;
  • English language proficiency

Benefits 

  • Equity at Nubank
  • Health insurance
  • Vacations of 15 workdays
  • NuLanguage - Language learning program
  • Parental leaves

Diversity and Inclusion

We want to have a product for everyone, and we build strong and diverse teams that rise to the challenge. We are a team of the most creative people in technology, and we hire under equal opportunity, irrespective of gender, ethnicity, religion, sexual orientation, or background. We are proud to say that 30% of Nubanker recognize themselves as part of the LGBTQ+ community, and 40% of our team comprises women in all positions and seniority levels. We are a very process-light organization that values human interactions, and that is an essential part of our culture. At Nubank, everyone has the opportunity to speak up and participate, grow, and share ideas.

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Demographic Information

We enable millions of people across Latin America to live better by empowering them to control their own money. We aim to build strong and diverse teams that rise to the challenge.

We are a team of the most creative people in technology. We hire under equal opportunity, irrespective of gender, ethnicity, religion, sexual orientation, or background. At Nubank, everyone has the chance to speak up and participate, grow, and share ideas.

To ensure we are continually building a more diverse and inclusive workplace that reflects the customers we serve and seek to empower, we hire based on the principle of equality. We consider gender, ethnicity, race, religion, sexual orientation, and other identity markers as enriching ingredients to our company while ensuring neither of them represent a barrier when recruiting talent.

Please share some additional information about yourself to assess our diversity and inclusion goals – it’s completely optional. Filling this demographic form will not affect your hiring process in any way. The data will be used for insights and metrics for internal process improvement only.

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