Credit Risk Lead

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 $1.8 trillion credit gap. Our mission is to unlock their potential by providing innovative financial solutions tailored to their needs.

R2 partners with leading platforms to embed financial services that SMBs can leverage effortlessly, starting with revenue-based financing. We are a tight knit team coming from organizations such as Amazon, Google, Uber, Mercado Libre, Globant, and J.P. Morgan. We are backed by world-class investors such as Gradient Ventures (Google’s AI-focused fund), General Catalyst, Hi Ventures, Cometa, Y Combinator, Femsa Ventures, Prosus, Endeavor Catalyst, among others.

We are seeking a highly skilled and innovative Credit Risk Lead to drive decision-making processes and optimize credit portfolio performance. The ideal candidate will combine expertise in data analysis, machine learning, and statistical modeling to enhance risk assessment, develop actionable insights, and improve operational efficiency. This role offers the opportunity to collaborate cross-functionally and influence strategic decisions at the core of our credit risk infrastructure.

Key Responsibilities:

1. Data Analysis:
   • Analyze large, complex datasets to uncover trends, patterns, and correlations that influence credit risk and financial performance.
   • Provide actionable insights to key stakeholders to improve risk management strategies.
   • Provide actionable insights that can be reflected in Credit Policy
2. Machine Learning & AI:
   • Develop and enhance predictive models using machine learning techniques to assess and mitigate credit risk.
   • Optimize algorithms to improve model performance and reduce risk exposure.
3. Portfolio Risk Assessment:
   • Collaborate with the risk management team to evaluate the risk profile of the credit portfolio.
   • Forecast future risk trends and recommend data-driven mitigation strategies.
4. A/B Testing:
   • Design and conduct A/B tests to evaluate the impact of new features on risk performance and adoption metrics.
5. Reporting & Visualization:
   • Prepare comprehensive reports, dashboards, and presentations to communicate findings and recommendations to executives, regulators, and other stakeholders.
6. Process Improvement:
   • Identify opportunities to streamline operational processes and enhance decision-making frameworks.
7. Collaboration:
   • Work closely with cross-functional teams, including credit risk, finance, and IT, to integrate models and data seamlessly into the organization’s risk infrastructure.

Requirements:

• Experience in developing and implementing machine learning models for risk assessment.
• Programming languages such as Python, R, or similar.
• Advanced SQL skills for querying and manipulating large datasets.
• Strong statistical thinking and the ability to translate data into actionable business insights.
• Experience in designing and analyzing A/B tests to inform strategic decisions.
• Excellent communication skills for presenting complex information to diverse audiences.
• Ability to work in a collaborative, fast-paced environment with a focus on innovation and results.

Preferred Qualifications:

• Familiarity with lending business and frameworks in credit risk management.
• Knowledge of visualization tools