What is the hiring process like for Data Science at Nubank?

Here’s everything you need to know about the role that Data Science plays at Nubank and how to join our team

Hiring for data science at Nubank

Nubank was created to fight the complexity of the financial system and empower people. We use Technology, Design, and Data Science to develop amazing products and services that help customers regain control over their finances.

As a fintech, having comprehensive processes backed up by data-informed decision making is crucial to our operations, meaning we can offer the right set of products to the right customer at the right time. That’s why we are always looking for talents to join our DS team.

We’ve created a process focused on both guaranteeing a good experience for every candidate and allowing us to learn more about each applicant.

But, before telling how it works, we’d like to talk a bit more about Data Science here at Nubank.

Data Science at Nubank

We are a data-informed company. Also, one of our core values is “we pursue smart efficiency.” That’s why Data Science plays an essential role in every aspect of our business: from the conversations we have with our customers through our products support to the credit limits we offer.

Our Data Science chapter is divided in:

  • Machine Learning Engineers: responsible for creating solutions that help to solve business problems using data analysis;
  • Data Scientists: they have two distinct profiles — one focused on business and another focused on technical challenges such as algorithms and data optimization.

You can find both Machine Learning Engineers and Data Scientists in different offices, products, and squads here at Nubank, as they support the customer lifecycle as a whole. Also, our Data Science team is composed of people with diverse backgrounds. We have physicists, economists, engineers, business analysts, and a lot more. This mix of different experiences is essential for us to continue to reinvent the financial system and create simple, fair, and genuinely human products.

What are data scientist working on

Despite all that, it’s still Day One for us, which means that we still have many other challenges to face. Ok, but what’s next? Although we have done some fantastic work so far, there are still many amazing opportunities ahead. To name a few examples, here are some things our Data Scientists have been working:

  • Feature Store for consolidating real-time data into reusable features that feed our predictive models;
  • Monitoring infrastructure that captures, stores and visualizes data that goes into and out of our predictive models;
  • Metadata management services built into our CI systems so we can keep track of every model deployment and their metadata;
  • Build the next generation of Fraud and Credit models, incorporating innovative data sources (e.g., combining structured and unstructured data) and using state-of-the-art techniques (e.g., sequence models, causal inference models);
  • Building testing and personalization capabilities for our products (Bandits, Reinforcement Learning, etc.).

And what is the interview process like?

Like everything we do at Nubank, our recruiting process also reflects our values. It goes like this:

1- Application and Resumé

The first step is applying for a position on our careers page.

Candidates can import data straight from LinkedIn, upload their CVs, and add other types of files and information. They also have to answer some initial questions — such as the very basic “Why are you interested in joining Nubank?”.

At this stage, we are interested in learning about the candidate’s previous experiences. We take a look at academic and work experience, as well as personal projects. We also want to understand their motivations — which is why we ask everyone to be transparent about their expectations joining Nubank. After all, our reality must fit the type of challenges that drives them.

If the candidate was actively recruited — on LinkedIn, for example –, we skip to the next phase.

2- Remote interview

People approved in the first phase are invited to a remote interview with either a recruiter or a Senior team member. At this stage, we hope to:

  • Understand more about the candidates, their professional backgrounds, their technical skills and what they are looking for in their career;
  • Explain how we apply Data Science and Machine Learning at Nubank;
  • Talk about the dynamics of our teams;
  • Assess how the candidate behaviors and how they can be a cultural addition to our company.

More than an interview, this meeting is meant to be a transparent conversation between the candidates and us — this is the time to get to know one another and share our expectations.

For Senior positions, we also have a second remote interview for those who were approved in the previous one. The candidate will talk to a Senior Member of the Data Science Chapter about topics related to leadership, ownership, and influence.

3- Technical Exercise

After the remote interview, we send candidates a technical exercise and usually give them around five days to finish it. It allows them to think about the problems and deliver good solutions.

The test is composed of:

  • For Data Scientists: one programming puzzle;
  • For Machine Learning Engineers: selected questions on Machine Learning;
  • A few open-ended questions.

A senior member of the Data Science team reviews the exercise. 

4- Face-to-face Meeting

Everyone approved in the technical exercise moves forward to the next phase: onsite interviews. At this stage, we:

  • Organize a series of interviews with our People & Culture team and talk about more specific technical and cultural aspects of working at Nubank;
  • Follow up on online test open questions to better understand some topics;
  • Do a pairing exercise for Machine Learning Engineers or a modeling case for Data Scientists.
  • Check on problem-solving skills.

At this stage, we are interested in understanding how the candidates work in pairs, listening to their ideas, and seeing how they act in situations that are very similar to those experienced by our teams daily.

5- Offer and Onboarding

We are delighted to extend a job offer to everyone approved on the final stage! If the candidate accepts it, we arrange all the details for the starting date and the onboarding — an immersion in our culture, business, and technology.

The onboarding is meant to provide every tool a Nubanker needs to begin working with us and contribute to our challenges!

(To know how was the remote onboarding during the first months of 2020, take a look at this post -in Portuguese)

Stay Restless. Join Nu.

We’re looking for individuals who are passionate about what they do and eager to solve complex problems at scale – all this while working in a safe, welcoming surrounding. We seek people who want their work to have a positive impact on the lives of millions of people who, otherwise, would be stuck in a bureaucratic and inefficient relationship with their money.

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