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.
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.
- 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 Data
By 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).
Top Skills
What We Do
RecargaPay is an all-in-one payments superapp based in Brazil that invites people to switch out of autopilot and rethink their finances based on convenience, affordability, and flexibility.
The platform streamlines payments for over 7 million Brazilians by consolidating credit and debit cards, instant payments like Pix, and Open Finance, on a mission to democratize mobile payments and financial services in Brazil.
Featuring services such as bill payments, mobile top-ups, public transportation, installment plans, and loans, designed with convenience, low cost and flexibility in mind. RecargaPay is changing the way both banked and unbanked Brazilians make their everyday payments and access their financial services.
Founded in 2010, having already received over $120 million in funding from investors that include IFC and IADB, RecargaPay is authorized as a Payments Institution and SCD by the Brazilian Central Bank.
