About the role
About Addi We are a leading financial platform, building the future of payments, shopping, and banking—a world where consumers and merchants can transact effortlessly and grow together. Today, we serve over 2 million customers and partner with more than 20,000 merchants, making Addi Colombia’s fastest-growing marketplace. With a state-of-the-art, technology-first approach, we provide banking solutions (deposits, payments, unsecured credit) and commerce services (e-commerce, marketing), bridging the financial gap for millions and redefining how people experience financial freedom. As the country’s leading Buy Now, Pay Later provider, we have secured regulatory approval to operate as a bank, unlocking even greater opportunities for our customers. In the past year, we have also achieved profitability, reinforcing the strength of our business model and our ability to scale sustainably. Our mission has earned the trust of world-class investors, including Andreessen Horowitz, Architect Capital, GIC, Goldman Sachs, Greycroft, Monashees, Notable Capital, Quona Capital, Union Square Ventures, Victory Park Capital, and more, who back our vision for the future. With their support, we are not just growing—we are transforming Latin America’s financial ecosystem and shaping the next generation to shop, pay, and bank in Colombia. But what truly sets us apart is how we build. We are a conscious company, driven by deep experience in scaling technology, services and products, and we live by our values every day. About the Role This is where you come in. Below, you’ll find what this role is all about—the impact you’ll drive, the challenges you’ll tackle, and what it takes to thrive at Addi. If you’re ready to be part of something big, keep reading. What’s the mission you’ll drive Protect Addi’s profitability and scalability by designing and deploying high-precision Credit Risk and Fraud models, while bridging the gap between traditional risk modeling and cutting-edge AI, building the automated systems that decide who to lend to and how to stop bad actors, while researching LLM applications to redefine the credit lifecycle. What you will do Develop and Implement ML Models : Participate actively in the entire ML model lifecycle—from business definitions to design, development, implementation, and monitoring. Work with cross-functional teams to ensure models meet both technical and business requirements. Manage Data Pipelines and Model Deployment : Collaborate with Data and Engineering teams to design and optimize data pipelines that support seamless model deployment to production. Ensure models are integrated properly, scalable, maintainable, and monitored in live environments. Monitor and Evaluate Model Performance : Continuously monitor performance and stability of production scores. Define success metrics, build evaluation methods (offline + online), and iterate to improve quality and reduce regressions. Conduct A/B Testing and Experimentation : Design and execute experiments (A/B tests, holdouts, phased rollouts) to validate the impact of models and strategies on business metrics. Analyze results to guide prioritization and continuous improvement. Collaboration and Knowledge Sharing : Work closely with interdisciplinary cross-functional teams (Risk, Fraud, Product, Engineering) to translate data insights into business-actionable strategies. Innovate and Explore AI/LLM Applications : Research and prototype new AI/LLM techniques for Lending—including applications like document processing, automated credit analysis support, fraud pattern recognition, and conversational tools. Stay curious and bring innovative ideas to the team. Improve Processes : Continuously propose ML techniques, algorithms, or tools that enhance Addi's customer understanding and risk management. What we’re looking for Proven Technical Tenure in Data Scientist in Lending 3+ years of full-time technical experience specifically in Data Science for Credit Risk or Fraud. Demonstrated history of delivering production-ready systems in a high-growth startup or fintech environment. Bachelor’s degree in a highly quantitative field (Mathematics, Statistics, Physics, Engineering, or Computer Science). Demonstrated ability to apply advanced mathematics and sampling techniques to solve real-world financial problems. Has Solid Proficiency in Modern Data Tooling Mastery of SQL for data management and Python (pandas, scikit-learn, xgboost) for advanced modeling and analysis. Experienced in working with semi-structured data and using Git/GitHub for professional code reviews and collaborative development. Experienced in End-to-End Model Deployment Track record of taking models from initial business definition through to "live" environment monitoring and iteration. Proven ability to diagnose system failures and regressions in production environments. Proven Experience in Lending & Fraud Modeling Demonstrates deep expertise in building supervised models for regression and classification specifically for Credit Scoring and Fraud Detection. Has a solid grasp of Colombian regulatory frameworks (e.g., provisioning and SARLAFT) and how they influence model design and documentation. Possesses Strong Statistical & Experimental Foundations Ability to design and execute rigorous A/B tests and hypothesis testing to validate the business impact of risk strategies. Mastery of model interpretability techniques (e.g., SHAP, LIME) to ensure "black box" models are transparent to stakeholders and regulators. Demonstrates Ability to Build Full-Stack ML Pipelines Skilled in collaborating with Engineering to design and optimize data pipelines that support seamless, scalable model deployment. Expert at building evaluation frameworks that include both offline performance indicators and online production monitoring. Track Record of Innovative AI/LLM Research Displays a genuine "learning mindset" by actively researching and prototyping how LLMs can solve lending-specific problems like automated document analysis. Ability to translate "hype" into practical, production-ready applications with clear quality and cost guardrails. Communicates Technical Complexity with Influence Varying the delivery of complex technical concepts so they are digestible for senior leadership, directly influencing high-stakes credit policy decisions. Actively seeks cross-functional feedback from Risk, Fraud, and Product teams to ensure models are "business-actionable." Why join us? Work on a problem that truly matters – We are redefining how people shop, pay, and bank in Colombia, breaking down financial barriers and empowering millions. Your work will directly impact customers' lives by creating more accessible, seamless, and fair financial services. Be part of something big from the ground up – This is your chance to help shape a company, influencing everything from our technology and strategy to our culture and values. You won’t just be an employee—you’ll be an owner Unparalleled growth opportunity – The market we’re tackling is massive, and we’re growing faster than almost any fintech lender at our stage. If you’re looking for a high-impact role in a company that’s scaling fast, this is it. Join a world-class team – Work alongside top-tier talent from around the world, in an environment where excellence, ownership, and collaboration are at the core of everything we do. We care deeply about what we build and how we build it—and we want you to be a part of it. Competitive compensation & meaningful ownership – We believe in rewarding our talent. You’ll receive a generous salary, equity in the company, and benefits that go beyond the basics to support your growth. How the hiring process looks like We believe in a fast, transparent, and engaging hiring experience that allows both you and us to determine if there's a great fit. Here’s what our process looks like: Step 1: People Interview (30 min) A conversation with a recruiter or hiring manager to get to know you, your experience, and what you're looking for. We’ll also share more about Addi, our culture, and the role. Step 2: Initial Interview (45-60 min) A more in-depth conversation with the hiring manager, where we explore your skills, experience, and problem-solving approach. We want to understand how you think and work. Step 3: Take Home Challenge (5-6 days) Complete a simple take-home challenge within a 1-week window. With this technical challenge, we want to see your technical expertise solving a real-world problem. We expect that you invest 5 hours or less in developing a working solution. Step 4: Take Home Challenge Review (60 min) Meet with a Data Scientists and the Data Science Lead to talk about your take-home exercise submission and any questions you might have. Step 5: Co-Founder Interview If there’s a strong match, you’ll have a final conversation with our Founder to align on expectations, cultural fit and ensure mutual excitement. From there, we’ll move quickly to an offer and discuss next steps. We value efficiency and respect for your time, so we aim to complete the process as quickly as possible. Our goal is to make this experience insightful and exciting for you, just as much as it is for us. Regardless of the outcome, we are committed to always providing feedback , ensuring that you walk away with valuable insights from your experience with us.