Data Scientist – Chapter DS Admisión

Role Overview

Join the best team and transcend with your talent as a Data Scientist – Chapter DS Admisión. Your main objective will be to lead projects and develop tools, methodologies, and analytical models that support retail risk management.

What You Will Do

Develop predictive and prescriptive models for retail banking risk management, using advanced analytics, Machine Learning, and cloud tools. Exploit databases and information sources to generate knowledge, data discovery, web scraping, data synthesis, and variable management for models and feature store.

Why It Might Be a Fit

Participate and propose innovation initiatives through technologies such as Machine Learning, Deep Learning, Text Mining, and GenAI. Be part of the model governance ecosystem, ensuring compliance with current regulatory regulations.

Requirements

• Professional in Statistics Engineering, Mechatronics Engineering, Systems Engineering, Computer Science, Software Engineering, Economics, Physics, Mathematics, or related careers.
• Desirable specialization or diploma in Data Science, Advanced Analytics, or related disciplines.
• Minimum 1 year of experience in Data Science.
• Knowledge of Big Data, Data Mining, Machine Learning, Credit Scoring, and management indicators.
• Experience in developing, calibrating, and monitoring analytical or risk models.
• Intermediate or advanced level of Python and SQL management.
• Knowledge of cloud tools (AWS or similar platforms) at an intermediate or advanced level.
• Knowledge of Credit Scoring methodologies, over-indebtedness, GenAI, and Agentic AI.
• Desirable knowledge of Model Risk Management and IFRS 9.
• Desirable certifications in Credit Scoring, Machine Learning, Deep Learning, Artificial Intelligence, AWS, or related technologies.

Benefits

• Access to development opportunities
• Continuous training
• Mentorship
• Promotion of digital transformation
• Participation in projects that promote digital change in the financial sector
• Equality of opportunities between men and women

Tagged as: Python, SQL