Data Scientist (Core ML & Analytics)
Who we are:
CloudWalk is a fintech company reimagining the future of financial services. We are building intelligent infrastructure powered by AI, blockchain, and thoughtful design. Our products serve millions of entrepreneurs across Brazil and the US every day, helping them grow with tools that are fast, fair, and built for how business actually works. Learn more at cloudwalk.io.
Who We’re Looking For:
We’re hiring a Data Scientist to help us drive decision-making and product innovation through careful experimentation, critical thinking, and applied machine learning.
You’ll work closely with engineers, researchers, and product teams to generate insights from data, design and run A/B tests, and train models that improve our products. This is a hands-on, full-stack data science role - from SQL and EDA to modeling and business impact analysis.
We’re looking for someone who knows how to think clearly with data, ask the right questions, and translate results into action. You don’t chase trends - you like when the data makes sense.
What You'll Do:
Explore product and system data to uncover opportunities, issues, or hypotheses.
Design and analyze A/B tests, working closely with product and growth teams.
Train, tune, and evaluate classical ML models (classification, regression, ranking).
Communicate findings clearly through writing, dashboards, and presentations.
Work with backend and infra teams to deploy and monitor your models.
Build reproducible workflows using tools like notebooks, scripts, and experiment tracking.
Contribute to a culture of curiosity, rigor, and patience in how we work with data.
What We’re Looking For:
Strong analytical skills: You know how to break down a question, test a hypothesis, and avoid false conclusions
Solid ML foundation: You’re comfortable training models, tuning them, validating results, and explaining decisions
Deep EDA and data handling: You can explore a dataset from all angles, understand distributions, spot leaks, and clean things up
Experimentation mindset: You’ve designed or analyzed controlled experiments and know when an A/B test makes sense — and when it doesn’t
Code quality: You write clean Python, use version control, and prefer reproducible work
Business awareness: You think about cost, value, trade-offs, and know when a heuristic beats a model
Communication skills: You can explain your thinking in writing and discussions, with clarity and precision.
Bonus Points:
Experience with causal inference or uplift modeling
Experience in product analytics or growth-focused DS
Experience working with Airflow, BigQuery, dbt, or similar data infra
Experience in training and shipping models to production
Familiarity with basic experimentation pitfalls (SRM, novelty effects, power issues).
How We Hire:
Online assessment: technical logic and fundamentals (Math/Calculus, Statistics, Probability, Machine Learning/Deep Learning, Code)
Technical interview: deep dive into theory and reasoning for fraud detection (no code)
Cultural interview
If you are not willing to take an online quiz, do not apply.
Data Scientist (Core ML & Analytics)
Who we are:
CloudWalk is a fintech company reimagining the future of financial services. We are building intelligent infrastructure powered by AI, blockchain, and thoughtful design. Our products serve millions of entrepreneurs across Brazil and the US every day, helping them grow with tools that are fast, fair, and built for how business actually works. Learn more at cloudwalk.io.
Who We’re Looking For:
We’re hiring a Data Scientist to help us drive decision-making and product innovation through careful experimentation, critical thinking, and applied machine learning.
You’ll work closely with engineers, researchers, and product teams to generate insights from data, design and run A/B tests, and train models that improve our products. This is a hands-on, full-stack data science role - from SQL and EDA to modeling and business impact analysis.
We’re looking for someone who knows how to think clearly with data, ask the right questions, and translate results into action. You don’t chase trends - you like when the data makes sense.
What You'll Do:
Explore product and system data to uncover opportunities, issues, or hypotheses.
Design and analyze A/B tests, working closely with product and growth teams.
Train, tune, and evaluate classical ML models (classification, regression, ranking).
Communicate findings clearly through writing, dashboards, and presentations.
Work with backend and infra teams to deploy and monitor your models.
Build reproducible workflows using tools like notebooks, scripts, and experiment tracking.
Contribute to a culture of curiosity, rigor, and patience in how we work with data.
What We’re Looking For:
Strong analytical skills: You know how to break down a question, test a hypothesis, and avoid false conclusions
Solid ML foundation: You’re comfortable training models, tuning them, validating results, and explaining decisions
Deep EDA and data handling: You can explore a dataset from all angles, understand distributions, spot leaks, and clean things up
Experimentation mindset: You’ve designed or analyzed controlled experiments and know when an A/B test makes sense — and when it doesn’t
Code quality: You write clean Python, use version control, and prefer reproducible work
Business awareness: You think about cost, value, trade-offs, and know when a heuristic beats a model
Communication skills: You can explain your thinking in writing and discussions, with clarity and precision.
Bonus Points:
Experience with causal inference or uplift modeling
Experience in product analytics or growth-focused DS
Experience working with Airflow, BigQuery, dbt, or similar data infra
Experience in training and shipping models to production
Familiarity with basic experimentation pitfalls (SRM, novelty effects, power issues).
How We Hire:
Online assessment: technical logic and fundamentals (Math/Calculus, Statistics, Probability, Machine Learning/Deep Learning, Code)
Technical interview: deep dive into theory and reasoning for fraud detection (no code)
Cultural interview
If you are not willing to take an online quiz, do not apply.