Carlos Alfredo Torres Cubilla
Data Scientist
Biography
Carlos Torres is a Data Scientist with a strong background in Statistics, Machine Learning, and Big Data Analytics.
He holds both a Bachelor’s degree in Statistics and a Master’s degree in Advanced Analysis of Multivariate Data and Big Data from the University of Salamanca, where he developed solid skills in programming, predictive modeling, and applied research.
Carlos has experience working with cloud platforms such as AWS and Databricks, where he has trained and deployed machine learning models for real-world applications. Previously, he worked at Banco General, where he developed data-driven solutions to optimize loan recovery and increase the bank’s profitability.
He is currently focused on expanding his expertise in advanced analytics and data-driven decision-making to develop impactful and efficient solutions, while continuing to explore new applications of artificial intelligence and machine learning in real-world contexts.
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- Statistics
- Artificial intelligence
- Machine learning
- Programming
Master's Degree in Advanced Analysis of Multivariate Data and Big Data, 2020
University of Salamanca
Bachelor's degree in Statistics, 2019
University of Salamanca
Technical skills
Development of machine learning models, task automation, and data analysis
Advanced statistical analysis, visualization, and predictive modeling
Building and deploying data and machine learning pipelines in collaborative environments
Experiment management and production deployment of machine learning models
Experience with S3, EC2, and QuickSight for cloud-based analytics
Version control, collaborative workflows, and reproducible development
Basic understanding to interpret and work with queries
Clear and structured technical documentation in reproducible environments
Basic knowledge of HTML structure for presenting results or integrating content
Power skills
Ability to analyze information and make data-driven decisions
Critical and creative approach to addressing complex challenges
Flexibility in dynamic environments and openness to new technologies
Commitment to lifelong learning and professional growth
Clarity and empathy when conveying technical and strategic ideas
Ability to motivate, guide, and coordinate teams toward common goals
Experience
Apr 2022 – Feb 2025
- Led strategic advanced analytics projects in banking, such as Delinquency Forecasting and Recovery Optimization, achieving substantial improvements in portfolio recovery and delinquency reduction.
- Developed and implemented machine learning models (Scikitlearn, LightGBM, XGBoost) deployed in production with scalable pipelines in Databricks and monitoring through MLflow.
- Designed robust ETL pipelines in PySpark to feed executive dashboards in AWS QuickSight, optimizing data-driven decision-making for senior managers.
- Mentored a team of data scientists and engineers, promoting data engineering and visualization standards aligned with international best practices.
Jan 2021 – Mar 2022
- Participated in end-to-end analytics projects such as predicting credit card churn, insurance sales, and next best product to buy, integrating predictive models directly into business processes for collections and risk.
- Automated ETL processes in PySpark and developed predictive models in Python, increasing the scalability and efficiency of analytical flows.
- Prepared financial reports with visualizations tailored to technical and non-technical audiences, facilitating the communication of findings and recommendations.
- Implemented ETL processes in R (Tidyverse) to consolidate and clean data from various sources.
- Developed and deployed an interactive application in Shiny for multivariate statistical analysis, improving data exploration and visualization.
- Created interactive HTML reports with dynamic visualizations, optimizing the communication of results to international clients.
- Advised students on the application of advanced statistical techniques to academic projects.
- Supported teaching in applied statistics courses, promoting the use of analytical tools and statistical software.
Projects
SparseBiplots
R package that performs the HJ-Biplot and modifications introducing Ridge, LASSO and Elastic Net penalty.
Covid-19 in Castilla & Leon
Web app to visualize the epidemiological status of COVID-19 in Castilla & León, Spain.
HackForGood 2019
Project carried out to solve the challenge of Artificial Intelligence for the improvement of the Health System.
Certifications
Recent Publications
Contact
- carlos221296@gmail.com
- Wedel, 22880