As a Data Scientist on our AI Optimization team, your mission is to design and optimize intelligent systems that power core product experiences. You'll transform rich data into models that drive automation, personalization, and smart decision-making at scale. This role blends applied science and analytics, focused on building adaptive ML systems that evolve continuously and make a tangible impact.
The AI Optimization Team
We work across the ML spectrum – from traditional statistical models to cutting-edge agentic systems
We collaborate with distributed, cross-functional teams of Engineers, Data Scientists, and Analysts in a culture that values open discussion and intellectual honesty
We experiment with emerging techniques to push the boundaries of real-world AI capabilities and system optimization
We value curiosity and ownership – the mindset of a researcher with the maturity to own both problems and outcomes
What You'll Do
Design and optimize ML models that power core product experiences and drive business outcomes
Develop statistical frameworks for A/B testing, performance monitoring, and measuring model effectiveness
Research and implement cutting-edge techniques to enhance model accuracy, speed, and reliability
Collaborate with product teams to optimize user experiences and translate insights into business strategy
Build evaluation pipelines to continuously monitor and improve model performance in production
What You'll Need
Strong statistical and ML foundation with experience in experimental design, hypothesis testing, and model optimization
Python proficiency with data science libraries (pandas, scikit-learn, numpy, scipy)
Machine learning expertise across supervised, unsupervised, and reinforcement learning approaches
SQL skills for data extraction, analysis, and feature engineering
Communication skills to translate analytical findings into clear business insights
Ability to communicate and debate in English and Portuguese
Nice to Have
App optimization experience with multi-armed bandits (MAB), recommendation systems, or personalization algorithms
Analytics platform experience with tools like Amplitude, Rudderstack, or similar product analytics platforms
MLOps familiarity with tools like MLflow for model tracking and experimentation
Experience with Google Cloud Platform and BigQuery for large-scale data analysis
Agentic frameworks experience with LangChain or similar tools for AI system development
Recruiting process outline:
Online assessment: An online test to evaluate your analytical skills and statistical reasoning
Technical interview: Deep dive into your ML experience and problem-solving approach
Cultural interview
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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