Data Scientist (Financial AI)

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 TeamWe’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 explainableWe push toward event-driven, AI-augmented decisioning where experiments directly shape credit limits, default rates, and merchant growthWe believe in data-driven democratization of access to capitalWe put curiosity first—exploring before exploitingWe solve puzzles that demand safety, compliance, explainability, and speed all at onceWhat You'll DoDesign and execute experiments for credit models, with rigorous frameworks to measure business and merchant impactBuild systematic experimentation infrastructure—metrics, statistical methodologies, and evaluation criteria for credit model performanceImplement A/B testing systems with proper statistical power, randomization, and causal inference methodsAnalyze results from multiple model variations, translating them into clear credit policy recommendationsDevelop scalable best practices balancing statistical rigor with business speedCollaborate with engineering to deploy and monitor experimental models in real-time decision engines, with rollback safety netsApply measurement science to link experiments to merchant success, default rates, and financial inclusion outcomesBridge offline insights to production systems through careful validation and gradual rollout strategiesTechnologies / Techniques UsedPython for analysis, modeling, and statistical computing (core language in our stack)SQL for large-scale feature engineering on financial datasetsGoogle Cloud Platform + BigQuery for analytics infrastructureStatistical modeling & experimental design for credit risk evaluationMachine learning frameworks for classification and risk modelingMLflow for deployment and monitoring in productionDocker & Kubernetes for orchestration with engineering teamsWhat You'll NeedCuriosity, initiative, and a bias toward experimenting and learning fastStrong experimental design expertise (A/B testing, causal inference, measurement frameworks)Statistical rigor: power analysis, bias detection, multiple testing correctionsPython proficiency for analysis, modeling, and statistical computationMeasurement science skills—designing metrics and building robust evaluation frameworksExperience with machine learning for classification and risk modelingSQL skills for feature engineering and large dataset analysisStrong communication skills in English & Portuguese, with ability to explain technical results to non-technical audiencesNice to HaveExperience with Google Cloud Platform and BigQueryHands-on work in credit model experimentation and measurement in production fintech/digital lending environmentsMLOps experience—deployment, monitoring, and experimentation at scaleBackground or experience in applied statistics or measurement science in business contexts (economics, operations research, etc.)Recruitment Process OutlineOnline Assessment – evaluating theory and logical reasoningTechnical Case Study – working with real-world financial data & experimentsTechnical Interview – discussion & case presentationCultural Interview – alignment with CloudWalk valuesIf 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.Originally posted on Himalayas

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