Data Scientist Analyst RappiPay

[CO] Bogotá

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Ya no tienes que salir de tu casa u oficina para disfrutar lo mejor de tu ciudad. Te llevamos cualquier cosa en minutos. Rappi llegó para cambiarte la vida.

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Rappi is one of the first Latin American unicorns and a start-up that continues to focus on growing and making life easier for our users. As a company, we seek to continue improving the services we already offer, add more to our offer and continue expanding throughout the Latin American continent.

Role Objective

  • We are looking for Data Scientists for the new financial ecosystem at RappiBank that will help us discover the information hidden in vast amounts of Rappi’s data, and help us make smarter decisions to deliver even better products. Your primary focus will be in applying data mining, doing statistical analysis, and building high quality prediction systems integrated with our products. As a Data Scientist at RappiBank, you will responsible for providing support to the different areas of the business: mainly fraud prevention and detection, risk management, growth and customer reach. The ideal candidate should be comfortable using large data sets to find opportunities in the market, for our customers and products, as well as to find process optimization opportunities. The candidate must have strong experience using a variety of data mining/analysis methods, data tools and frameworks, as well as implementing, building, and testing data models. You will collaborate in a very rich and talented environment of Data Scientists, Data Engineers, and stakeholders throughout the globe to create impact in the business. We are looking for a passionate professional who wants to change the financial world as we know it.


  • Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets. Experience with data handling and manipulation such as Pandas. Experience cleansing, analyzing, and exploiting data. Understanding of financial data is a plus. Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks. Experience training, validating, and taking the models into production is a plus. Best practices for software development is a plus. A drive to learn and master new technologies and techniques. 
He leído y acepto la Autorización de Datos Personales de Rappi S.A.S a la Política de Tratamiento de Datos Personales
I have read and accept the Authorization of Personal Data from Rappi S.A.S accordance with the Personal Data Treatment Policy
Job region(s): South America
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