Join the Fintech revolution and build the future of finance in Mexico! Responsibilities The primary goal of the Data Scientist in Risk Management is to develop, implement, and maintain machine learning models and algorithms to enhance underwriting processes and customer management strategies. This role involves continuous improvement and experimentation with models and working closely with the Lead or Manager Data Scientist. Model Development and Implementation: Design, develop, and implement machine learning models and algorithms for underwriting and customer management. Model Improvement: Conduct experiments to enhance existing models, ensuring their accuracy and reliability through rigorous testing, validation, and benchmarking. Analytics and Communication: Apply advanced analytical methodologies to solve complex business challenges, presenting insights through charts and graphs, and communicating findings to non-technical stakeholders. Qualifications Degree in a quantitative discipline (e.g., Actuary, Mathematics, Physics, Statistics, Computer Science, or related field). At least 2 years of proven experience in Data Science. Knowledge and experience with Machine Learning models. Knowledge of SQL. Experience in production programming in Python and the Pandas library & AWS SageMaker. Statistics fundamentals: most common distributions, generalized linear models, hierarchical models (desirable), A/B testing, bootstrap, experiment design, simulation. Advanced English (must). Benefits A dynamic and collaborative work environment that encourages personal development. Opportunities to learn and grow professionally using cutting‑edge technologies. A passionate and talented team to share knowledge and experiences. A competitive compensation package and attractive benefits. Opportunity to positively impact the lives of thousands of people and contribute to the development of the country. #J-18808-Ljbffr