Miguel A.

Data Scientist

Spain

Trusted member since 2025

7 years of experience

Over his career, Miguel has made significant contributions at IBM, Banco Santander, and Atos, including authoring four patents in natural language processing and deep learning. He has been recognized as a winner of the HackThatStartup Datathon, and also serves as a competition juror for IBM’s AI challenges.

Miguel has driven performance gains of up to 30% across systems, and has successfully overseen cross‑functional teams in delivering enterprise-scale data products. He holds certifications from Microsoft, AWS, and IBM, and is currently pursuing a PhD at the Polytechnic University of Catalonia. Bringing together deep technical mastery and business insight, Miguel is dedicated to driving innovation and creating impactful AI solutions.

Main expertise

Google Cloud6 years

Azure5 years

AWS4 years

MySQL7 years

30+

Experience4

Senior Data Scientist

IQVIA•

Healthcare

Apr 2022 · 4y 6m

Led AI/ML initiatives, including the development of demand forecasting models for pharmaceutical products, which reduced forecasting errors by 20% and improved supply chain reliability.
Designed and deployed a medicine-matching system using NLP and deep learning, optimized prescription processing, and improved patient outcomes.
Developed end-to-end ML pipelines in Databricks and Azure ML, ensured scalable and reproducible workflows for large-scale healthcare datasets.
Improved the performance of existing models by up to 30% through advanced hyperparameter tuning, feature engineering, and model optimization.

AWS

Databricks

Apache Spark

Python

AWS Lambda

15+

Senior Data Scientist

Banco Santander•

Banking and Finance

Jan 2021 - Mar 2022 · 1y 2m

Designed ML models for fraud detection and risk scoring, which reduced false positives by 15% while strengthening fraud prevention.
Applied deep learning techniques to optimize credit scoring models, which increased approval rates without compromising risk exposure.
Introduced Spark-based pipelines to handle high-frequency transactional data, enabling faster insights and decision-making.

MySQL

AWS

Apache Spark

Python

AWS Lambda

11+

Data Scientist

IBM•

Information Technology (IT) and Services

Jan 2017 - Dec 2020 · 3y 11m

Developed NLP and deep learning solutions, which resulted in four patents filed in areas such as conversational AI, text summarization, and automated classification.
Built production-grade ML pipelines for enterprise clients, improved model explainability, and increased adoption in regulated industries.
Collaborated with IBM Research teams to accelerate the integration of deep learning techniques into client-ready products.

AWS

Python

AWS Lambda

AWS S3

Azure

13+

Data Scientist

Atos•

Information Technology (IT) and Services

Sep 2015 - Dec 2016 · 1y 3m

Pioneered deep learning research projects, which resulted in patent applications focused on neural network optimization and semantic search.
Applied machine learning models to large enterprise datasets, delivering predictive insights that improved client decision-making.
Collaborated with R&D teams to design scalable architectures for ML deployment in production environments.
Participated in European research consortia on AI, contributing to scientific publications and collaborative knowledge sharing.

MySQL

Apache Spark

Python

Azure

Data Science

Engineering excellence

All Data Scientists who have applied to Proxify are scored from 0 to 300 on engineering excellence, one of the five parameters we evaluate. This score reflects engineering excellence only, based on interviews, take-home assignments, live coding sessions, and/or on-the-job performance reviews. The curve shows how all evaluated Data Scientists are distributed across that range, where our acceptance threshold for this parameter sits, and where Miguel stands.