Data Scientist (Financial AI)

Posted 120 days ago

Job Description

This job posting has expired and no longer accepting applications.

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.

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