We are redirecting you to the source. If you are not redirected in 3 seconds, please click here.

Data Scientist (Financial AI) at CloudWalk. Location Information: Brazil. At . CloudWalk. , we're building the best payment network on Earth (then other planets 🚀). We’re an . AI-first fintech unicorn. bringing justice to Brazil's broken payment system. We work in a traditional financial sector—but we aim to . break conventions. with bold, innovative thinking.. We’re looking for a . Data Scientist. who sees experiments not as tests, but as . conversations with reality. . You’ll design, run, and analyze . credit experiments. that shape real-time lending decisions, helping millions of Brazilian entrepreneurs access fairer credit.. The Financial AI Team. We’re part of CloudWalk’s Financial Services domain, powering . money movement and credit decisions. —including real-time credit engines, repayment orchestration, dynamic pricing, and collections.. We build and run scoring models, underwriting systems, and pricing logic that keep credit decisions . fast, fair, and explainable. We push toward . event-driven, AI-augmented decisioning. where experiments directly shape credit limits, default rates, and merchant growth. We believe in . data-driven democratization. of access to capital. We put . curiosity first. —exploring before exploiting. We solve puzzles that demand . safety, compliance, explainability, and speed. all at once. What You'll Do. Design and execute. experiments for credit models, with rigorous frameworks to measure business and merchant impact. Build . systematic experimentation infrastructure. —metrics, statistical methodologies, and evaluation criteria for credit model performance. Implement . A/B testing systems. with proper statistical power, randomization, and causal inference methods. Analyze results. from multiple model variations, translating them into clear credit policy recommendations. Develop . scalable best practices. balancing statistical rigor with business speed. Collaborate with engineering to . deploy and monitor. experimental models in real-time decision engines, with rollback safety nets. Apply . measurement science. to link experiments to merchant success, default rates, and financial inclusion outcomes. Bridge . offline insights. to . production systems. through careful validation and gradual rollout strategies. Technologies / Techniques Used. Python. for analysis, modeling, and statistical computing (core language in our stack). SQL. for large-scale feature engineering on financial datasets. Google Cloud Platform. + . BigQuery. for analytics infrastructure. Statistical modeling & experimental design. for credit risk evaluation. Machine learning frameworks. for classification and risk modeling. MLflow. for deployment and monitoring in production. Docker & Kubernetes. for orchestration with engineering teams. What You'll Need. Curiosity, initiative,. and a bias toward experimenting and learning fast. Strong . experimental design. expertise (A/B testing, causal inference, measurement frameworks). Statistical rigor. : power analysis, bias detection, multiple testing corrections. Python proficiency. for analysis, modeling, and statistical computation. Measurement science skills. —designing metrics and building robust evaluation frameworks. Experience with . machine learning. for classification and risk modeling. SQL skills. for feature engineering and large dataset analysis. Strong communication skills in . English & Portuguese. , with ability to explain technical results to non-technical audiences. Nice to Have. Experience with . Google Cloud Platform. and . BigQuery. Hands-on work in . credit model experimentation. and measurement in production fintech/digital lending environments. MLOps. experience—deployment, monitoring, and experimentation at scale. Background or experience in . applied statistics. or . measurement science. in business contexts (economics, operations research, etc.). Recruitment Process Outline. Online Assessment. – evaluating theory and logical reasoning. Technical Case Study. – working with real-world financial data & experiments. Technical Interview. – discussion & case presentation. Cultural Interview. – alignment with CloudWalk values. If you are not willing to take an online quiz and work on a test case, do not apply.. Diversity and inclusion:. We believe in social inclusion, respect, and appreciation of all people. We promote a welcoming work environment, where each CloudWalker can be authentic, regardless of gender, ethnicity, race, religion, sexuality, mobility, disability, or education.