We are the financial technology company in Mexico that has helped more than 70k customers to make their plans come true.
Our purpose is to support small and medium enterprises in the country to fulfill their dreams, through our solutions (financing, credit card and payments) to help solve their main problems, seeking to be the best ally of entrepreneurs, contributing to the community, the country and the world
About the Role
We are looking for a detail-oriented data scientist with a strong background in statistics and/or mathematics to help us lift our risk and collection modeling to the next level. We value self-starters that proactively look for improvements and new ideas.
Working in a multi-disciplinary environment and communicating your results and insights in a clear manner comes naturally to you.
- Build predictive models from development through testing and monitoring, for customer acquisition, underwriting, and customer management.
- Explore and test new data sources, algorithms and model features to improve our risk and collections models or to identify growth opportunities.
- Develop insights and data visualizations to solve complex problems, and communicate ideas to internal stakeholders.
- Processing, cleansing, and verifying the integrity of data used for analysis.
- Creating automated reports in order to track models performance in a timely and
- accurate manner.
- Collaborate with data engineers and ML engineer to develop automated orchestration of data implemented and model pipelines
- Document the methodology used, results obtained, in a clear manner for
- reproducible research and help other team members to solve problems in a faster way.
- Train and mentor junior team members Data & ML engineers and Data Scientists.
- Strong knowledge of Python and SQL
- Degree in a quantitative field (Statistics, Mathematics, Computer Science, or related field).
- Knowledge of traditional machine learning models, supervised and unsupervised.
- Experience working with Risk and Collections models.
- Statistics fundamentals: most common distributions, generalized linear models, hierarchical models (desirable), A/B testing, bootstrap, experiment design, simulation.
- Strong self-management, drive, and organization.
- The ability to multi-task in a fast-paced environment is essential.
- Knowledge of Bayesian modeling
- Experience in the financial sector