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 (starting with revenue-based financing and buy now pay later for business customers). We are a tight knit team coming from organizations such as Google, Nubank, Uber, McKinsey & Co., Mercado Libre, Globant, J.P. Morgan, Clip, and Ualá. We are backed by world-class investors such as Gradient Ventures (Google’s AI-focused fund), General Catalyst, Y Combinator, Femsa Ventures, PayU, among others.
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.
- Process transactional data with various approaches, including feature-based and time-series, approaches.
- Stating hypotheses and testing them using basic statistical tests.
- Building supervised models (such as regression and classification models), and unsupervised models (such as clustering and dimensionality reduction models), mostly aligned with the credit risk capability.
- Collaborate in the development of deployment frameworks for machine learning models at scale.
Who you are
- You have at least two years of experience with data science in theoretical and practical levels.
- You have strong programming abilities (structured, object-oriented, and/or event-oriented programming) and are very comfortable programming in Python/R and SQL.
- You have strong statistical and mathematical knowledge, including linear algebra, calculus, and statistical inference, among other topics.
- You have built regression and/or classification models in the past for solving financial problems.
- You are comfortable consuming data through APIs, SFTP, or straight-up CSVs.
- You have deployed machine learning models in cloud architectures (AWS preferably) in the past.
- You have an owner mindset: you care about getting to the bottom of how to make a startup successful.
- You understand every problem as an opportunity for analyzing and learning.
To be considered a strong candidate, you (besides the former points):
- Know how to implement machine learning pipelines, from data acquisition to model deployment.
- Have worked with unsupervised learning techniques, such as clustering and/or dimensionality reduction.
- Have stated and tested hypothesis (such as normality and causality) using the appropriate testing frameworks.
**Does this position sound like a good fit? Apply at the link below:
https://r2capital.bamboohr.com/jobs/view.php?id=36&source=bamboohr
R2
