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 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.