Data Scientist Specialist

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. Do you want to challenge the limits of data science in a high-impact, growing environment? At RecargaPay, we are looking for a Specialist Data Scientist to join our Data Science team, with the mission of supporting the development, monitoring, and evolution of credit models and decision strategies. As a Specialist Data Scientist, you will be responsible for leading the development and implementation of advanced machine learning models and analytical solutions to solve complex credit and transaction risk challenges. You will be part of the Data Science team, focusing on technical leadership, mentoring, and the adoption of new technologies. Responsabilities Develop and implement real-time scoring models to quantify the risk level of transactions and credit operations. Build predictive models using internal and third-party data to optimize user onboarding and reduce losses. Evolve static rule engines into dynamic, graph-based ones, enabling more intelligent and adaptable rule management. Lead the adoption of new technologies like Databricks and Data Catalogue, advocating for best practices and facilitating a transition to a more modern and efficient data environment. Analyze large volumes of transactional, user behavior, and demographic data to identify patterns, trends, and opportunities for improvement in risk assessment. Develop and implement fingerprinting and geographic tracking solutions to improve risk assessment. Guide and mentor team members, sharing your experience and knowledge, and leading key projects from a technical perspective. Monitor and analyze the performance of credit models, focusing on their stability and accuracy. Requirements 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: Demonstrated experience in building and implementing machine learning models. Deep knowledge of classification, regression, and clustering algorithms, as well as feature engineering and model selection techniques. Experience with model explanation techniques like SHAP, bivariate analysis, and weight of evidence. Data Analysis: Ability to handle large datasets and write efficient, optimized SQL queries. 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. Basic 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. Problem-Solving Orientation: The ability to research existing solutions in other contexts and adapt them to the specific problem you are working on. 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. 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. Competitive and market-aligned salary. Remote work — wherever you are, you’re part of the team Home office allowance through a monthly deposit in the RecargaPay app. Health and dental plans with no co-pay. Life insurance. Flexible meal allowance (via Flash). TotalPass membership to take care of your health. Spanish or Portuguese classes. Diversity & Inclusion at RecargaPay At RecargaPay, you’ll have the freedom to be who you are because we believe that diverse perspectives and experiences make us more creative and stronger. Here, everyone is welcome to express themselves authentically. We value the richness of each journey and the multiple ways of seeing the world, without distinctions of gender, race, sexual orientation, age, religion, or any other characteristic that makes us unique.About the use of your DataBy sharing your resume with us, you authorize the use of your data for analysis during the selection process and possibly for other opportunities within the RecargaPay group. You can request the update or deletion of your information at any time, in accordance with LGPD (General Data Protection Law). #J-18808-Ljbffr