Data Scientist

São Paulo, State of São Paulo, Brazil · Data Science


Why do we hire data scientists?

Nubank is a technology company that has set out to completely rethink financial services in Brazil. We need world-class data scientists (and modelers, statisticians, AI practitioners, machine learning engineers) to build proprietary algorithms that predict responsiveness to marketing, credit risk, fraud likelihood and many other types of customer behavior to get us there.

What are some examples of problems a data scientist solves?

At Nubank, we don’t shy away from using the latest and greatest machine learning algorithms and techniques; in fact, we encourage them. We have a rich dataset with natural language text, images, graphs, and much more, as well as more traditional sources of financial data. We also have an almost endless set of models to build, including everything from credit scoring to text tagging. Below are just a few of the problems a Nubank data scientist might solve:


You will fit well if

You will experience an early stage startup culture in a truly diverse and international environment. We believe in good team chemistry, flat hierarchy, enthusiasm for creating things, and our surprising capacity to learn new things when we stay humble and open-minded. A quantitative academic background with advanced degrees and English language proficiency are helpful.

Desired skills and experience

We are excited to meet data scientists with various areas of experience – there is no single ideal profile. We believe there is room for very diverse skill sets to add value:

  1. 3+ years of relevant professional or academic experience in a highly quantitative field (e.g. statistics, computer science, mathematics, physics, genetics, econometrics, biostatistics)


  1. Multiple notable finishes in machine learning competitions
  2. Experience working with languages that support statistical learning (e.g. Python, R, Scala)
  3. An advanced ability to work on distributed cloud platforms and interact with databases


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