<div><span>At </span><b>CloudWalk</b><span>, were building the best payment network on Earth (then other planets 🚀). We’re an </span><b>AI-first fintech unicorn</b><span> bringing justice to Brazils broken payment system. We work in a traditional financial sector—but we aim to </span><b>break conventions</b><span> with bold, innovative thinking.</span></div><div><br /></div><div><span>We’re looking for a </span><b>Data Scientist</b><span> who sees experiments not as tests, but as </span><b>conversations with reality</b><span>. You’ll design, run, and analyze </span><b>credit experiments</b><span> that shape real-time lending decisions, helping millions of Brazilian entrepreneurs access fairer credit.</span></div><h3>The Financial AI Team</h3><ul><li>We’re part of CloudWalk’s Financial Services domain, powering <b>money movement and credit decisions</b>—including real-time credit engines, repayment orchestration, dynamic pricing, and collections.</li><li>We build and run scoring models, underwriting systems, and pricing logic that keep credit decisions <b>fast, fair, and explainable</b></li><li>We push toward <b>event-driven, AI-augmented decisioning</b> where experiments directly shape credit limits, default rates, and merchant growth</li><li>We believe in <b>data-driven democratization</b> of access to capital</li><li>We put <b>curiosity first</b>—exploring before exploiting</li><li>We solve puzzles that demand <b>safety, compliance, explainability, and speed</b> all at once</li></ul><h3>What Youll Do</h3><ul><li><b>Design and execute</b> experiments for credit models, with rigorous frameworks to measure business and merchant impact</li><li>Build <b>systematic experimentation infrastructure</b>—metrics, statistical methodologies, and evaluation criteria for credit model performance</li><li>Implement <b>A/B testing systems</b> with proper statistical power, randomization, and causal inference methods</li><li><b>Analyze results</b> from multiple model variations, translating them into clear credit policy recommendations</li><li>Develop <b>scalable best practices</b> balancing statistical rigor with business speed</li><li>Collaborate with engineering to <b>deploy and monitor</b> experimental models in real-time decision engines, with rollback safety nets</li><li>Apply <b>measurement science</b> to link experiments to merchant success, default rates, and financial inclusion outcomes</li><li>Bridge <b>offline insights</b> to <b>production systems</b> through careful validation and gradual rollout strategies</li></ul><h3>Technologies / Techniques Used</h3><ul><li><b>Python</b> for analysis, modeling, and statistical computing (core language in our stack)</li><li><b>SQL</b> for large-scale feature engineering on financial datasets</li><li><b>Google Cloud Platform</b> + <b>BigQuery</b> for analytics infrastructure</li><li><b>Statistical modeling &amp; experimental design</b> for credit risk evaluation</li><li><b>Machine learning frameworks</b> for classification and risk modeling</li><li><b>MLflow</b> for deployment and monitoring in production</li><li><b>Docker &amp; Kubernetes</b> for orchestration with engineering teams</li></ul><h3>What Youll Need</h3><ul><li><b>Curiosity, initiative,</b> and a bias toward experimenting and learning fast</li><li>Strong <b>experimental design</b> expertise (A/B testing, causal inference, measurement frameworks)</li><li><b>Statistical rigor</b>: power analysis, bias detection, multiple testing corrections</li><li><b>Python proficiency</b> for analysis, modeling, and statistical computation</li><li><b>Measurement science skills</b>—designing metrics and building robust evaluation frameworks</li><li>Experience with <b>machine learning</b> for classification and risk modeling</li><li><b>SQL skills</b> for feature engineering and large dataset analysis</li><li>Strong communication skills in <b>English &amp; Portuguese</b>, with ability to explain technical results to non-technical audiences</li></ul><h3>Nice to Have</h3><ul><li>Experience with <b>Google Cloud Platform</b> and <b>BigQuery</b></li><li>Hands-on work in <b>credit model experimentation</b> and measurement in production fintech/digital lending environments</li><li><b>MLOps</b> experience—deployment, monitoring, and experimentation at scale</li><li>Background or experience in <b>applied statistics</b> or <b>measurement science</b> in business contexts (economics, operations research, etc.)</li></ul><h3>Recruitment Process Outline</h3><ul><li><b>Online Assessment</b> – evaluating theory and logical reasoning</li><li><b>Technical Case Study</b> – working with real-world financial data &amp; experiments</li><li><b>Technical Interview</b> – discussion &amp; case presentation</li><li><b>Cultural Interview</b> – alignment with CloudWalk values</li><div>If you are not willing to take an online quiz and work on a test case, do not apply.</div></ul><div><b>Diversity and inclusion:</b></div><div><span>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.</span></div>