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Sr. Data Science Analyst 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.. Responsabilities. As a Senior Data Scientist on Product team, you will be responsible for:. ● Develop and implement advanced machine learning models to quantify the risk level of transactions and credit operations, and optimize user onboarding and reduce losses.. ● Design and conduct complex data analyses on large volumes of transactional, user behavior, and demographic data to identify patterns, trends, and opportunities for model enhancement.. ● Optimize and maintain existing credit models, ensuring their stability, accuracy, and business impact through continuous monitoring and refinement.. ● Lead the design and execution of A/B tests and other experiments related to credit decision strategies, translating results into actionable business recommendations.. ● Build and optimize robust and scalable data pipelines for model training, inference, and performance monitoring.. ● Contribute to the adoption of best practices in data science, including model documentation, version control (Git), and code quality. Requirements. ● . Experience. in data science, with a proven track record of independently developing and deploying machine learning models in a production environment. . ● . Programming and Tools: . Proficiency in Python, SQL, and Spark. Experience with libraries such as Pandas, NumPy, Matplotlib, and Scikit-learn. Familiarity with platforms like Databricks, AWS, and Azure. Experience with Git for version control and collaboration.. ● . Analytical Modeling & Machine Learning: . Strong experience in building and implementing machine learning models. Solid knowledge of classification, regression, and clustering algorithms, as well as feature engineering and model selection techniques. Experience with model explanation techniques.. ● . Data Analysis: . Ability to handle large datasets and write efficient, optimized SQL queries. Strong experience with exploratory data analysis and evaluating model features.. ● . Statistical Knowledge:. Strong understanding of A/B testing and statistics, including experimental design and statistical significance. Proficient knowledge of predictive modeling metrics like AUC, KS, precision, and recall.. ● . Other Skills:. Knowledge of data modeling principles and experience building robust and scalable data models. An analytical mindset with a strong focus on problem-solving. Strong mathematical skills with the ability to optimize . complex problems.. ●. Innovative Thinking:. Applying theoretical knowledge of statistics, economics, and behavioral finance to optimize proposed solutions.. ● . Communication: . Ability to translate complex technical findings into actionable business insights and communicate them clearly to both technical and non-technical audiences.. ● . Collaboration: . Willingness to work in a collaborative and dynamic environment, actively contributing to team knowledge sharing.. . Bonus Points. ● Proficiency with PySpark for distributed data processing in large-scale environments.. ● Experience with MLOps and deploying machine learning models into production.. ● 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.