RecargaPay
Finance / FinServ
DataScientistSpecialist(Lending)
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Data Scientist Specialist (Lending) at RecargaPay. Skills: Machine learning models, Credit models, Risk assessment, Data analysis, Python, SQL, Spark. Development, monitoring, and evolution of credit models and decision strategies. Leading the development and implementation of advanced machine learning models and analytical solutions to solve complex credit and transaction risk challenges”
Industry & Context.
Analytical mindset with a focus on problem-solving; Ability to research existing solutions in other contexts and adapt them to the specific problem you are working on; Solve real problems
What They're Looking For.
Must Have
Proficiency in Python, Proficiency in SQL, Proficiency in 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, Demonstrated experience in building and implementing machine learning models, Deep knowledge of classification, regression, and clustering algorithms, Knowledge of feature engineering, Knowledge of model selection techniques, Experience with model explanation techniques like SHAP, bivariate analysis, and weight of evidence, Ability to handle large datasets, Ability to write efficient, optimized SQL queries, Experience with exploratory data analysis, Experience evaluating model features, Understanding of A/B testing, Understanding of statistics, Understanding of experimental design, Understanding of statistical significance, Basic knowledge of predictive modeling metrics like AUC, KS, precision, and recall, Knowledge of data modeling principles, Experience building robust and scalable data models, Analytical mindset with a focus on problem-solving, Mathematical skills with the ability to optimize complex problems, Ability to research existing solutions in other contexts and adapt them to the specific problem you are working on, Applying theoretical knowledge of statistics, economics, and behavioral finance to optimize proposed solutions, Ability to translate complex technical findings into actionable business insights and communicate them clearly to both technical and non-technical audiences, Willingness to work in a collaborative and dynamic environment
Nice to Have
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, Exposure to credit bureau data, Exposure to behavioral features, Previous experience in fintechs or financial services companies
What You'll Do.
and evolution of credit models and decision strategies
Leading the development and implementation of advanced machine learning models and analytical solutions to solve complex credit and transaction risk challenges
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
Analyze large volumes of transactional
and demographic data to identify patterns
and opportunities for improvement in risk assessment
Develop and implement fingerprinting and geographic tracking solutions to improve risk assessment
Monitor and analyze the performance of credit models
focusing on their stability and accuracy
How You'll Work.
Team & Collaboration
Work with teams; Guide and mentor team members, sharing your experience and knowledge; Lead key projects from a technical perspective; Willingness to work in a collaborative and dynamic environment
Communication Scope
Ability to translate complex technical findings into actionable business insights and communicate them clearly to both technical and non-technical audiences
Process & Methodology
Leading key projects from a technical perspective
Full Job Description
**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.** ### Position Overview 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. ### Key Responsibilities * 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 rul
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