Alberto Saborido Patiño – Physicist | Data Scientist
Presentation
I am passionate about physics and the cutting-edge methods involved in its research. My studies have awakened in me a special interest in data analysis, data science, and simulation methods. I am also highly interested in detector and electronics studies, a field in which I had the opportunity to work as a research intern. I have specialized in experimental methods in particle physics, completing an internship and my bachelor’s degree thesis within the international collaboration of the LHCb experiment. I am currently pursuing an international master’s degree in particle physics. I have also combined my studies in physics with applying my technical knowledge in the industry. These experiences have given me, in addition to extensive technical knowledge, strong communication and teamwork skills. I like to face new challenges and enjoy stepping out of my comfort zone.
Professional Experience
Software Developer
Lars Grönberg – IT Beratung, Dortmund, Germany
April 2024 – August 2024
- Developed containerized applications for data analysis using Docker and Apache Superset.
- Orchestrated processes with Microsoft Power Automate.
Data Analyst
SDG Group, Santiago de Compostela, Spain
June 2022 – July 2023
- Developed and maintained data analysis applications with Redshift and QlikSense.
- Worked on data modeling using DBT as data transformation tool (ETL and ELT) and Snowflake as a cloud data warehouse.
- Utilized Python and other general-purpose programming languages for analysis and data transformation.
Research Intern
Galician Institute of High Energy Physics (IGFAE), Santiago de Compostela, Spain
June 2021 – September 2021
- Worked on a LHCb Vertex Locator (VELO) prototype, focusing on radiation interaction studies and data acquisition systems.
- Analyzed data collected from the VELO module using Monte Carlo simulations.
- Incorporated new functionalities into the detector’s data acquisition system.
Skills
Technical Skills
- Programming: Python, C++, SQL, Jinja, Docker
- Data Analysis: Scikit-learn, PyTorch, TensorFlow, ROOT (open-source data analysis framework for high energy physics developed at CERN)
- Data Tools: Snowflake, Redshift, DBT, Qlik Sense, Apache Superset
- Miscelaneous:
- Good understanding and implementation of machine learning and deep learning algorithms
- Good knowledge of databases and data modeling
- Experienced in using Linux and Bash
- Experienced in using remote servers and SSH for analyzing large datasets.
- Basic knowledge of quantum computing and Qskit (open-source framework for creating and running quantum algorithms)
Soft Skills
- Hardworking and proactive
- Excellent communication and teamwork, experienced in international collaborations
Languages
- Spanish: Native
- Galician: Native
- English: Full professional proficiency (C1 Advanced Cambridge Certificate)
Education
International Master of Advanced Methods in Particle Physics
TU Dortmund University, University of Bologna, University Clermont-Auvergne
September 2023 – September 2025
Diplôme Universitaire Data Scientist
University Clermont-Auvergne, France
September 2023 – May 2024
Bachelor’s Degree in Physics
University of Santiago de Compostela, Spain
September 2017 – February 2022
- Thesis: “Analysis of Charged Particle Multiplicity Associated with 𝜙 Mesons in Proton-Nucleus Collisions at the LHCb Experiment” – Grade: 9.8/10
Physics Degree (Academic Year Abroad)
University of Bucharest, Romania
September 2019 – June 2020
Complementary Training
- International School Of High Energy Physics – Institut d’Études Scientifiques de Cargèse – March 2024
- Machine Learning Specialization – DeepLearning.AI & Stanford University (Coursera) – January 2023
- Introduction to Data Science – AFI Finance School – April 2022
- SQL: Basic to Complex Queries – Udemy – March 2022
- Introduction to Quantum Computing – University of Santiago de Compostela – January 2022
- Scientific writing course – University of Santiago de Compostela – September 2021
- ELI (Extreme Light Infrastructure) Summer School Online Course – Bucharest – August 2021
- Introductory course on neural networks and their use in particle physics – Galician Institute of High Energy Physics – May 2020