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.
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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
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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)
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SQL for large-scale feature engineering on financial datasets
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Google Cloud Platform +
BigQuery for analytics infrastructure
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Statistical modeling & experimental design for credit risk evaluation
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Machine learning frameworks for classification and risk modeling
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MLflow for deployment and monitoring in production
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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)
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Statistical rigor: power analysis, bias detection, multiple testing corrections
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Python proficiency for analysis, modeling, and statistical computation
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Measurement science skills—designing metrics and building robust evaluation frameworks
- Experience with
machine learning for classification and risk modeling
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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
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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
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Technical Case Study – working with real-world financial data & experiments
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Technical Interview – discussion & case presentation
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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.
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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.
