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Remote Data Scientist (Financial AI) en Cloudwalk

Cloudwalk · São Paulo, Brasil · Remote

Python

SQL

Docker Container Platforms

Kubernetes Container Platforms

Google Cloud Platform

MLOps

Cloud

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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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