Pablo Olivares Martínez

ML Engineer | Data Scientist

pablolivares1502@gmail.com

Madrid, ES

Summary

ML Engineer and Data Scientist selected for the Santander Data Science Talent Program. Proven ability to apply deep learning and achieve impactful results in data projects, along with a strong foundation in Mathematics and Computer Science.

Work Experience

ML Engineer | Data Scientist at Santander Bank

2024-06 - Present

Madrid, Spain

  • Developed an LLM explainability solution for predictive models by identifying key features from underlying data to justify commercial opportunities.
  • Designed and implemented scalable data pipelines using PySpark for efficient data ingestion for model training.
  • Developed a health insurance subscription prediction model achieving 92% AUC, leading to a 23% increase in customer acquisition.
  • Designed and implemented a data quality control system for a Customer 360 project, improving data integrity and process execution time by up to 97%.

Education

Master of Science in Big Data & Business Analytics at Escuela de Organización Industrial (EOI), Spain

2024-06 - Current
  • Big Data Architecture
  • Data Visualization
  • Natural Language Processing

Bachelor of Science in Mathematics at University of Granada, Spain

2019-09 - 2024-07
  • Functional Analysis
  • Numerical Methods
  • Differential Equations

Bachelor of Science in Computer Science at University of Granada, Spain

2019-09 - 2024-07
  • Computer Vision
  • Metaheuristics
  • Artificial Intelligence

Erasmus+ Programme in at University of Łódź, Poland

2022-09 - 2023-07
  • Machine Learning
  • Operations Research
  • Statistical Inference
  • Stochastic Processes

Projects

Topological Data Analysis in CNNs

Explored the integration of Topological Data Analysis (TDA) with convolutional neural networks (CNNs) to enhance understanding of CNN data manipulation, resulting in improved classification accuracy and generalization.

  • Applied persistent homology techniques to analyze data structure during CNN processing.
  • Proposed topological regularization in models like EfficientNet-B0 and DenseNet-121.
  • Awarded 'Best Bachelor Thesis 2024 Promotion' for outstanding work.

Semantic Segmentation for Urban Mobility

Developed a deep learning solution for parking space detection in the city of Granada using semantic segmentation techniques, contributing to urban planning and mobility improvement.

  • Created an image segmentation dataset with a novel data augmentation technique tailored for parking detection.
  • Implemented architectures like PSPNet and DeepLabV3+, achieving an 80% F1-score in validation.

Skills

  • Programming: Python, SQL, C/C++, Java, LaTeX, R
  • Machine Learning & Data Science: Large Language Models (LLMs), Natural Language Processing (NLP), Convolutional Neural Networks (CNNs), Computer Vision, Deep Learning, Imbalanced Data, MLOps
  • Technologies & Tools: Azure Databricks, Spark, PyTorch, MLflow, OpenCV, Scikit-learn, Git, Jira, Confluence

Languages

  • Spanish - Native
  • English - Proficient (C1 Cambridge)
  • French - Independent

Volunteer Experience

Member and Collaborator at LibreIM

2021-02 - Present

Developed and maintained extensive LaTeX notes for LibreIM, a non-profit organization, focusing on Formal Logic and Topology.

Private Tutor at Busca Tu Profesor

2021-09 - 2022-06

Conducted mathematics and basic programming lessons for high school students while managing college studies.

Member at Imhlala Panzi Scouts

2012 - 2019

Organized charity and environmental tasks including natural environment cleanups, charity collections to aid minorities, awareness campaigns, and social inclusion activities.