Data Scientist - Risk (Científico de Datos - Riesgo) - Bogota (Hybrid)

Ready to accelerate your career? Clara is the fastest-growing company in Latin America. We've built the leading solution for companies to make and manage all their payments. We already help over 20,000 large and growing businesses operate with agility and financial clarity through locally issued corporate cards, bill pay, financing, and a powerful B2B platform built for scale. Clara is backed by some of the most successful investors in the world, including top regional VCs like monashees, Kaszek, and Canary, and leading global funds like Notable Capital, Coatue, DST Global Partners, ICONIQ Growth, General Catalyst, Citi Ventures, SV Angel, Citius, Endeavor Catalyst, and Goldman Sachs - in addition to dozens of angel investors and local family offices. We’re building the financial infrastructure that powers high-performing organizations across the region. We invite you to join us if you want to be part of a fast-paced environment that will accelerate your career and support you to do some of the best work of your life alongside a passionate and committed team distributed across the Americas. What you'll do We're looking for a Data Scientist to join our Risk Data Science team. In this role, you will be instrumental in analyzing complex datasets to generate insights that drive critical business decisions, specifically within credit risk, fraud prevention, and churn reduction. You will work cross-functionally to design, build, and deploy data-driven strategies that ensure Clara continues to scale securely and efficiently. Define and solve complex problems: Collaborate with cross-functional teams to identify business challenges, propose end-to-end solutions, and execute strategies that align with company objectives. Drive data understanding and insights: Explore and interpret large datasets using SQL and Python to identify patterns, anomalies, and trends. You will translate these findings into actionable insights that support informed decision-making. Build and deploy predictive models: Design, develop, and monitor machine learning models using Databricks , MLflow , scikit-learn , and PyTorch . You will follow the CRISP-DM methodology to ensure rigorous modeling standards from conception to production. Ensure data quality and integrity: specific responsibilities include cleaning and transforming raw data to ensure it is suitable for analysis, applying data quality checks, and maintaining validation rules. Innovate and automate: Continuously monitor model performance and data drift while staying updated on advancements in AWS cloud infrastructure and statistical methods to refine our analytical approaches. Who you are We’re looking for someone who meets the minimum requirements to be considered for the role. The preferred qualifications are a bonus, not a requirement. Must haves 5+ years of experience in data science or analytics, with a minimum of 2 years of hands-on experience developing risk models (e.g., credit, fraud, or churn). Strong technical proficiency in Python and SQL for data manipulation, querying, and statistical analysis. Proven experience working with cloud-based platforms, specifically AWS and Databricks . Hands-on experience with ML platforms and libraries such as MLflow , scikit-learn , and PyTorch . Working proficiency in English and Spanish. Strong problem-solving abilities with the capacity to communicate complex modeling processes to non-technical stakeholders. A degree in Data Science, Computer Science, Mathematics, Statistics, or equivalent practical experience. Adaptability to fast-changing, high-growth environments. Nice to haves Experience with data visualization tools such as Metabase . Solid understanding of data engineering concepts and ETL processes. Experience taking data workflows or models from development to production. Master’s degree in Data Science or a related field. Basic proficiency in Portuguese (or a desire to learn it). Why join ... (truncated, view full listing at source)