Who we are:

At R2, we believe that small and medium businesses are the productive engine of society. Small and medium businesses (SMBs) make up over 90% of companies in Latin America, yet they face a trillion-dollar credit gap. Our mission is to unlock SMBs’ potential by providing financial solutions that are tailored to their needs. We are reimagining the financial infrastructure of Latin America - where SMBs financial needs are satisfied without ever having to go to a bank.

R2 enables platforms in Latin America to embed financial services that SMBs can then leverage at the point of need and within the operating tools they use. We are a tight knit team coming from organizations such as Google, Amazon, Nubank, Uber, Mercado Libre, J.P. Morgan, Capital One and Ualá. We are backed by world-class technology investors such as Gradient Ventures (Google’s AI-focused fund), General Catalyst, and Y Combinator.

We are a data-first company. Data is the core of our product and the lifeblood for all of our decision-making. Data Interns sit at the helm of R2 by analyzing in a descriptive, predictive, and prescriptive way the data patterns, enabling new financial opportunities to thousands of companies across Latin America.

What you’ll work on:

• Building data structuring, cleaning, and enriching processes from a wide variety of data sources.
• Making descriptive analysis of merchant-related and transactional-related data, generating high-impact insights for business decision-making.
• Process transactional data with various approaches, including feature-based and time-series, approaches.
• Executing data science operational procedures to deliver high-quality results that help thousands of businesses in Latin America have access to capital.

Who you are:

• You have at least one year of experience with data analysis in a theoretical and practical way.
• You have strong programming abilities (structured, object-oriented, and/or event-oriented programming) and are comfortable programming in Python/R and SQL.
• You have a data-oriented mindset: you care about getting to the bottom of how to make decisions based on data.
• You understand every problem as an opportunity for analyzing and learning.

To be considered a strong candidate, you (besides the former points):

• Have built regression and/or classification models in the past for solving financial problems.
• Are comfortable consuming data through APIs, SFTP, or straight-up CSVs.