We are redirecting you to the source. If you are not redirected in 3 seconds, please click here.

Modeling Analyst II (Data Scientist) at RecargaPay. Come Make an Impact on Millions of Brazilians!. At RecargaPay, we’re on a mission to deliver the best payment experience for Brazilian consumers and small businesses — by building a powerful digital ecosystem where the banked and unbanked connect, and where consumers and merchants have a one-stop shop for all their financial needs.. We serve over 10 million users and process more than USD 4 billion annually. We’ve been profitable since 2022 and operate our own credit business. We are an AI-first, 100% remote team, scaling in the rapidly changing Brazilian financial market.. Our goal? Deliver the best payment experience in Brazil for people and small businesses alike.. We value autonomy, ownership, and a bias for action. We’re looking for people who are curious, hands-on, and driven by impact — who want to solve real problems, work with strong teams, and rethink what’s possible.. If you’re ready to do your best work, at scale, with purpose — this is your place.. Responsibilities. As a Modeling Analyst on Data Science team, you will be responsible for:. . Monitor and analyze the performance of credit models, focusing on stability, accuracy, and business impact.. . Support the design, execution, and analysis of A/B tests and other experiments related to credit decision strategies.. . Maintain organized data structures and technical documentation (data books, variable dictionaries, version control).. . Perform backtesting analyses using bureau data, identifying patterns and opportunities for segmentation.. . Conduct exploratory data analysis to support new modeling initiatives or model updates.. . Analyze and evaluate model features, including univariate, bivariate analysis and feature drift monitoring.. . Assist in building reusable analytical pipelines for scalable and sustainable insights.. . . Advanced SQL: ability to handle large datasets and write efficient, optimized queries.. . Python: experience with libraries like Pandas, NumPy, Matplotlib, and Scikit-learn.. . Experience with ML algorithms: logistic regression, random forest, gradient boosting, etc.. . Models explanation: SHAP, bivariate analysis, weight of evidence, etc.. . Databricks: familiarity with collaborative notebooks, workflows, and Delta Lake integration.. . Git: version control, repository organization, and collaboration best practices.. . Data visualization and communication: ability to translate technical findings into actionable business insights.. . A/B testing and statistics: solid understanding of experimental design and statistical significance.. . Basic knowledge of predictive modeling: understanding of metrics such as AUC, KS, precision, and recall.. . Analytical mindset and results-oriented, with a strong focus on problem-solving.. . Passion for innovation and experimentation.. . Knowledge of data modeling principles and experience in building robust and scalable data models.. . Strong mathematical skills and ability to optimize complex problems.. . Experience in activities related to data science.. . Bonus Points. . Proficiency with PySpark for distributed data processing in large-scale environments.. . Experience with MLOps in machine learning projects.. . Familiarity with model monitoring in production environments.. . Exposure to Open Finance, credit bureau data, or behavioral features.. . Previous experience in fintechs or financial services companies.. . Company Location: Brazil.