Data Science Specialist

EBANX is one of the most successful fintechs to emerge from Latin America — and today, we are building a truly global payments company. Our mission has remained constant from day one: to unlock access and enable companies and consumers to participate in the digital economy, no matter where they are.

What started as a bold vision has grown into a platform that connects some of the world’s largest digital businesses with customers across 21 of the fastest-growing markets. We operate where complexity exists — turning local challenges into global opportunities, and building the infrastructure that allows payments to move further, faster, and smarter.

We are a team of builders and problem-solvers. We think globally, act with curiosity, and believe diversity of thought is a competitive advantage.

As EBANX enters its next phase of hyper growth, we are looking for people who want to shape the future of payments, expand what’s possible, and help connect businesses and consumers across borders.
Let’s build what’s next — together.

At EBANX’s Data team you don’t just work with numbers. You transform information into intelligence that drives strategic decisions and directly impacts the digital payments revolution on a global scale. Every analysis combines curiosity, rigor, and collaboration, making our work truly Out of the Ordinary.

• As an AI Engineer Specialist your mission will be to own the design and deployment of scalable AI systems in production.

Your day-to-day impact:

• Own the end-to-end design, development, evaluation, and deployment of Machine Learning and AI solutions, ensuring scalability, reliability, and performance;
• Develop and optimize Machine Learning models, with a strong focus on classical Machine Learning techniques such as XGBoost, Random Forest, and Decision Trees, ensuring robustness, explainability, and efficiency;
• Build models and strategies focused on fraud prevention, chargeback risk, and risk prevention in credit card payments;
• Translate business and payment-related challenges into effective Machine Learning solutions, considering both technical performance and business impact;
• Build and maintain production-grade solutions for AI applications, including APIs, data pipelines, and services, in collaboration with AI Engineering and MLOps specialists;
• Implement and oversee continuous integration and continuous delivery (CI/CD) pipelines for AI model deployment and updates;
• Collaborate closely with data scientists, AI engineers, MLOps specialists, software engineers, and stakeholders across teams to translate business requirements into actionable AI solutions;