Develop, train, and validate statistical and machine learning models to support decision-making;
Analyze large volumes of structured and unstructured data, ensuring data quality and consistency;
Design and maintain data pipelines and modeling processes;
Collaborate with business teams to understand problems and formulate data-driven solutions;
Document and present analysis results and models to both technical and non-technical stakeholders;
Work on the governance and reproducibility of analytical models.

Degree in Statistics, Mathematics, Data Science, Engineering, Economics, or related fields (Bachelor's or Master's completed);
Proven prior experience in financial institutions, credit bureaus, and/or analytical consultancies;
Proficiency in languages such as SQL and Python for data manipulation, analysis, and modeling;
Experience developing and validating Machine Learning models (classification, regression, clustering, etc.);
Knowledge of Text Analysis, Natural Language Processing (NLP), or Generative Artificial Intelligence;
Familiarity with libraries such as pandas, scikit-learn, statsmodels, among others;
Strong analytical skills, critical thinking, and ability to communicate with stakeholders;
Solid and proven experience in AI, NLP, and ML;
Experience with MLOps frameworks.

Senior Data Scientist, MLOps

Key skills