About me
As a seasoned data scientist with a rich background in physics research, I bring a unique blend of analytical expertise and leadership skills to the table. With over 9 years of experience, my journey spans from being a researcher at CERN to my current data scientist role at HP.
Over these years, I developed a strong proficiency in analyzing large datasets using statistical tools and developing machine learning solutions. I excel at leading teams, eliciting requirements, prioritizing tasks and proposing data-driven solutions.
Additionally, I have a solid background in software development, having developed, maintained, and tested software solutions throughout my career.
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My background in physics has also equipped me with the skills to formulate hypotheses and design experiments, which I leverage as a data scientist.
Experience
Data Scientist @ HP
Since September 2024
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End-to-end development of Machine Learning solutions to improve sales across different business units
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Extraction of data-driven insights enabling decision making
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Identification of business needs and stakeholder management
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As a member of the Data Science for Guided Selling team, I actively participate in the interview process for new candidates, contributing to the selection of talented professionals who align with our team's goals
Senior Research Fellow @ CERN
April 2021 - April 2023
Member of the ATLAS Collaboration
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Coordinated a team of data scientists and physicists (30 people) [April 2022 - April 2023]:
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​Successfully managed 7 deliverables simultaneously
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Released data-driven recommendations to teams of data scientists
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- ​Planned and prioritized tasks in JIRA
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Monitored the progress of the tasks
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Flagged potential problems and proposed solutions
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Provided technical guidance on Python, C++ and statistics
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Organized and facilitated weekly meetings
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Reported regularly to group coordinators
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Managed people remotely
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Assigned roles and responsibilities
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Maintained documentation
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Ensured transfer of knowledge
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Analyzed data to extract data-driven corrections
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Streamlined a process to efficiently delete deprecated data
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Developed software (Python/C++):
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Led the development of a new release of a tool designed to clean large datasets and extract relevant information. This tool was successfully used to promptly inspect data from the 2022 ATLAS operations.
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Developed tests using continuous integration (CI) for early detection of issues and bugs
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Developed 2 solutions based on machine learning (deep learning):
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Implemented and deployed a neural network to predict the position of a particle in a detector. Improved previous estimation by up to 60%. [using NumPy, Pandas and Keras]
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Trained and optimized a model to identify physical particles. Improved performance by up to 50%. [Docker, Kubernetes and Kubeflow pipelines]
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Led 2 teams (5-7 people each) using statistical tools for data analysis:
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Supervised data analyzers and ensured high-quality software and measurements
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Preprocessed and cleaned large datasets to extract relevant information
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Performed precision measurements of physical quantities and estimated uncertainties
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Performed a maximum likelihood estimation to find the parameters of a data-driven statistical model
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Monitored storage space and enhanced documentation on storage and computing resources for the CERN ATLAS Team
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Organized 3 sessions in an internal (ATLAS only) workshop [44 participants]:
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Planned scope and content of sessions and selected speakers
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Chaired an Editorial Board:
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Reviewed the scope, strategy and results of a data analysis
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Identified problems and proposed solutions
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Research Associate @ McGill University
December 2018 - April 2021
Member of the ATLAS Collaboration
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Coordinated a team of software developers and physicists (18 people) [June 2019 - June 2021]:
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Successfully drove the development of a real-time data-driven decision-making software deployed in the ATLAS operations in 2022
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Elicited requirements and understood the needs of data scientists
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Defined the strategy of the group and provided estimates of required effort
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Planned, prioritized and monitored tasks and bugs in JIRA
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Ensured successful delivery of projects within scope and timeline
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Monitored the development process to ensure requirements and quality standards were met
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Managed people remotely
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Managed and resolved dependencies with other teams
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Developed, optimized and validated software algorithms and monitored their performance
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Organized and facilitated weekly meetings
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Reported software readiness, quality and performance to group coordinators
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Flagged potential problems and proposed solutions
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Developed tools for data cleaning, processing and monitoring
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Developed tools used to identify patterns in data
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Led 2 teams (5-7 people each) using statistical tools for data analysis:
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Supervised data analyzers and ensured high-quality software and measurements
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Preprocessed and cleaned large datasets to extract relevant information
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Performed precision measurements of physical quantities and estimated uncertainties
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Performed a chi-square goodness of fit test for hypothesis testing
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Member of an Editorial Board:
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Reviewed the scope, strategy and results of a data analysis
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Identified problems and proposed solutions
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Approved and drove publication of scientific results: ATLAS-CONF-2020-022.pdf
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Successfully edited and published scientific results: The European Physical Journal C volume 81
PhD candidate / PhD @ University of Buenos Aires (UBA)
Member of the ATLAS Collaboration
April 2014 - December 2018
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Liaison between a performance group and a physics group [duration: 2 years]
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Ensured smooth communication and collected user feedback
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Led 2 teams (5-7 people each) conducting data and performance analyses:
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Successfully produced and published scientific results: Journal of High Energy Physics 2018
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Monitored data analysis processes and ensured high-quality software and measurements
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Analyzed experimental data to extract physical quantities and validate simulation results
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Preprocessed and cleaned large datasets to extract relevant information
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Derived data-driven corrections and estimated uncertainties
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Performed a test statistic based on a profile likelihood ratio for hypothesis testing
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Developed and maintained software used by hundreds of users to apply corrections:
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Collected user feedback and provided user support
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Taught undergraduate biophysics courses
- Contributed to 3 scientific publications by doing data analyses:
MSc candidate @ Pierre Auger Observatory
April 2012 - April 2014
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Developed a simulation of a Surface Detector and studied its response under various scenarios
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Developed and maintained a calibration mechanism for the AMIGA muon detectors
Certifications
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Machine Learning, Data Science and Deep Learning with Python [October 2022]
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The Project Management Course: Beginner to PROject Manager [February 2023]
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Agile Fundamentals: Including Scrum & Kanban [March 2023]
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Business Analysis Fundamentals [March 2023]
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Become a Product Manager [March 2023]
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AWS Essentials [March 2023]
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Develop the Skills to Drive Innovation in Your Organization [June 2023]
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Learning Cloud Computing: Core Concepts [July 2023]
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Learning SQL programming [August 2023]
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Intermediate SQL for Data Scientists [August 2023]
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Tableau for Data Scientists [November 2023]
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Advanced Google Analytics [December 2023]
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Apache PySpark by Example [October 2024]
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Spark for Machine Learning & AI [April 2025]
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Resilience Training for Researchers [October 2021]
Other
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Machine Learning Summer School [June 2018]
Technical skills
Software development and Data Science:
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Python for data manipulation (PySpark, Pandas and NumPy), data visualization (matplotlib, Plotly and seaborn), automated testing (Pytest) and machine learning and statistical methods (SciPy, statsmodel, Keras from tensorflow, Scikit-learn)
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Business Intelligence / Analytics tools: Tableau and Looker Studio
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C++
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Git [GitLab and GitHub] and Continuous Integration
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Docker
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Kubernetes [Kubeflow]
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SQL
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Jupyter notebook
Software:
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JIRA
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Visual Studio Code, Vim
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Microsoft Excel/PowerPoint and Google Sheets/Slides
Website analytics and user behaviour:
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Google Analytics
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Google Search Console
Operating systems:
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Linux and Windows
Volunteering and outreach activities
ATLAS International MasterClasses
The ATLAS International Masterclasses are one day-long program for high-school students to provide them hands-on experience in particle physics.
Moderator in 3 video conferences at CERN
March 2019
The purpose was to interact with up to 5 groups of students (aged 16-19) from different schools around the globe. Each video conference contained:
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Presentation of the results from the measurement performed by the students using ATLAS data
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Discussion of the presented results
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Session of Q&A (questions and answers about particle physics, life at CERN, etc)
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Fun Quiz
Supervisor during hands-on experience
May 2018 and April 2017
Supervision of high-school students during the hands-on experience in the course of the ATLAS International MasterClasses taking place at University of Buenos Aires.
September 2013
Vocational guidance talk
Vocational guidance talk for high-school students at Colegio San Esteban in San Carlos de Bariloche, Argentina.
Talks
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8 talks given at national or international physics conferences
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Participated in several internal (ATLAS-only) workshops and meetings by organizing and chairing sessions, and giving talks.​
Hobbies
In my free time, I like taking on challenging board games, puzzles and video games. For example, I love playing strategy board games [1] such as "Terraforming Mars" and "Dune Imperium". Additionally, I enjoy playing escape room games [2]. ​Furthermore, I like trying new cooking recipes, watching TV series and movies, travelling and exploring new cities and places. ​[1] A strategy game is a game in which the players' decision-making skills have a high significance in determining the outcome. Strategy games often require decision tree analysis, or probabilistic estimation in the case of games with chance elements [source: wikipedia.org]. [2] An escape room is a game in which a team of players discover clues, solve puzzles, and accomplish tasks in one or more rooms in order to accomplish a specific goal in a limited amount of time. The goal is often to escape from the site of the game. Most escape games are cooperative but competitive variants exist [source: wikipedia.org].