is a startup founded in 2017 by three partners with years of experience in the Machine Learning and Artificial Intelligence market, having worked for large Brazilian corporations in the most varied fields.


  • Autonomy: We encourage a culture of feedback, though always responsibly.
  • Collaboration: We support transparency and communication among all interested parties.
  • Commitment: We encourage fast and simple problem-solving without outsourcing our responsibilities.
  • Humility and Excellence: We present solutions in a simple and accessible way.
  • Antifragile: We are able to learn from our mistakes and/or any problems that we encounter.
  • Challenges: We are persistent and enjoy challenges, offering sustainable deliverables, and creating real value for our clients.


  • To inspire decisions with simple and accessible answers to complex questions.


A team of advanced degree graduates, specialists in Credit, Anti-Fraud, Debt Collection, Propensity, and Churn.

We use our own products internally and the most advanced Big Data technology.

Atomization and scalability of modeling and real-time monitoring processes


We follow the General Data Protection Regulation guidelines.

Ease of use. Now everyone can create predictive models.


Holds a degree in Aeronautical Engineering from the São Carlos School of Engineering of the University of São Paulo (USP). Holds a Master’s in quantitative finance from the Getúlio Vargas Foundation (FGV) and is currently preparing to defend his Ph.D. thesis at the Polytechnic School of the University of São Paulo (Poli-USP) on Machine Learning with a focus on medical imaging. Author of “Econometrics with Eviews – An Essential Guide to Concepts and Applications”.

Machine Learning Professor in the Administration Institute Foundation’s MBA and graduate courses on Data Mining and Big Data. Started his career at Embraer modeling aerodynamic phenomena, then moved on to the financial market. Worked as an analyst at Rio Bravo Investments and the Ambipar Group, as well as a Data Scientist at Itaú. Developed predictive credit, anti-fraud, and insurance-focused models for Itaú.

Founded an urban logistics startup called 99motos in October 2014, which went on to merge with Rapiddo in 2016 and was eventually sold to iFood in September of 2018. Co-founder of two startups focused on Machine Learning: DataRisk (risk analysis) and RadSquare (medical applications).


Holds an undergraduate degree and a Master’s in Statistics from the University of São Paulo, as well as a Ph.D. from the Computer Science Department of the University of São Paulo (USP). Worked at the Research and Development department of Itaú Bank for five years, with Machine Learning and Statistic Models, and participated in the bank’s first Big Data project. Worked at Nubank for another four years as its Lead Data Scientist, helping build the credit department by developing the first versions of approval models. Has been teaching Machine Learning at the Administration Institute Foundation since 2015, in the LabData MBA, extension, and graduate courses.


Holds a Master’s in applied mathematics from the University of São Paulo (USP), having previously worked at Itaú and Neoway, and has been in Data Science for over ten years. Works with several different statistical and mathematical techniques, tools, and languages like python, R, hadoop, spark, etc., in addition to relational and nonrelational databases. Currently in charge of Datarisk’s technology departments.

Which are the most promising startups in the coming years?

What we do

Datarisk develops products and solutions by using advanced Artificial Intelligence and Machine Learning algorithms. Among these, of most note are our:

  • Predictive modeling platform [auoML]
  • OCR’s [documents, balance sheets, tax returns]
  • Consulting services to understand and solve your problems with customized solutions.
  • Anti-fraud Solutions
  • Automated product registration