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About me

As a physics researcher at CERN, I analyzed data in high volumes using statistical tools, led teams and prioritized their tasks, identified problems and proposed solutions through critical thinking and data insights, formulated hypotheses and designed experiments to prove them, elicited requirements, and I developed, maintained and tested software.

Languages

English

Spanish

Fluent

Native

Italian

B1

Education

PhD in Physics | June 2018

MSc in Physics | March 2014

  • LinkedIn
  • GitHub

Location

Barcelona, Spain

Experience

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Data Scientist @ HP

Since September 2024

  • Development of machine learning solutions

CERN logo

Senior Research Fellow @ CERN

April 2021 - April 2023

Member of the ATLAS Collaboration

  • Coordinated a team of data scientists and physicists (30 people) [April 2022 - April 2023]:

    • ​Successfully managed 7 deliverables simultaneously

      • Released data-driven recommendations to teams of data scientists

    • ​Planned and prioritized tasks in JIRA
    • Monitored the progress of the tasks

    • Flagged potential problems and proposed solutions

    • Provided technical guidance on Python, C++ and statistics

    • Organized and facilitated weekly meetings

    • Reported regularly to group coordinators

    • Managed people remotely

    • Assigned roles and responsibilities

    • Maintained documentation

    • Ensured transfer of knowledge

    • Analyzed data to extract data-driven corrections

    • Streamlined a process to efficiently handle data deletion

  • Developed software (Python/C++):

    • 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.

    • Developed tests using continuous integration (CI) for early detection of issues and bugs

  • Developed 2 solutions based on machine learning (deep learning):

    • 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]

    • Trained and optimized a model to identify physical particles. Improved performance by up to 50%. [Docker, Kubernetes and Kubeflow pipelines]

  • Led 2 teams (5-7 people each) using statistical tools for data analysis:

    • Supervised data analyzers and ensured high-quality software and measurements

    • Preprocessed and cleaned large datasets to extract relevant information

    • Performed precision measurements of physical quantities and estimated uncertainties

    • Performed a maximum likelihood estimation to find the parameters of a data-driven statistical model

  • Monitored storage space and enhanced documentation on storage and computing resources for the CERN ATLAS Team

  • Organized 3 sessions in an internal (ATLAS only) workshop [44 participants]:

    • Planned scope and content of sessions and selected speakers

  • Chaired an Editorial Board:

    • Reviewed the scope, strategy and results of a data analysis

    • Identified problems and proposed solutions

McGill logo

Research Associate @ McGill University

December 2018 - April 2021

Member of the ATLAS Collaboration

  • Coordinated a team of software developers and physicists (18 people) [June 2019 - June 2021]:

    • Successfully drove the development of a real-time data-driven decision-making software deployed in the ATLAS operations in 2022

    • Elicited requirements and understood the needs of data scientists

    • Defined the strategy of the group and provided estimates of required effort

    • Planned, prioritized and monitored tasks and bugs in JIRA

    • Ensured successful delivery of projects within scope and timeline

    • Monitored the development process to ensure requirements and quality standards were met

    • Managed people remotely

    • Managed and resolved dependencies with other teams

    • Developed, optimized and validated software algorithms and monitored their performance

    • Organized and facilitated weekly meetings

    • Reported software readiness, quality and performance to group coordinators

    • Flagged potential problems and proposed solutions

    • Developed tools for data cleaning, processing and monitoring

    • Developed tools used to identify patterns in data

  • Led 2 teams (5-7 people each) using statistical tools for data analysis:

    • Supervised data analyzers and ensured high-quality software and measurements

    • Preprocessed and cleaned large datasets to extract relevant information

    • Performed precision measurements of physical quantities and estimated uncertainties

    • Performed a chi-square goodness of fit test for hypothesis testing

  • Member of an Editorial Board:

    • Reviewed the scope, strategy and results of a data analysis

    • Identified problems and proposed solutions

    • Approved and drove publication of scientific results: ATLAS-CONF-2020-022.pdf

  • Successfully edited and published scientific results: The European Physical Journal C volume 81

UBA logo

PhD candidate / PhD @ University of Buenos Aires (UBA)

Member of the ATLAS Collaboration

April 2014 - December 2018

  • Liaison between a performance group and a physics group [duration: 2 years]

    • Ensured smooth communication and collected user feedback

  • Led 2 teams (5-7 people each) conducting data and performance analyses:

    • Successfully produced and published scientific results: Journal of High Energy Physics 2018

    • Monitored data analysis processes and ensured high-quality software and measurements

    • Analyzed experimental data to extract physical quantities and validate simulation results

    • Preprocessed and cleaned large datasets to extract relevant information

    • Derived data-driven corrections and estimated uncertainties

    • Performed a test statistic based on a profile likelihood ratio for hypothesis testing

  • Developed and maintained software used by hundreds of users to apply corrections:

    • Collected user feedback and provided user support

  • Taught undergraduate biophysics courses

  • Contributed to 3 scientific publications by doing data analyses:
Pierre Auger Observatory logo

MSc candidate @ Pierre Auger Observatory

April 2012 - April 2014

  • Developed a simulation of a Surface Detector and studied its response under various scenarios

  • Developed and maintained a calibration mechanism for the AMIGA muon detectors

Technical skills

Software development and Data Science:

  • Python for data manipulation (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)

  • Business Intelligence / Analytics tools: Tableau and Looker Studio

  • C++

  • Git [GitLab and GitHub] and Continuous Integration

  • Docker

  • Kubernetes [Kubeflow]

  • SQL

  • Jupyter notebook

Software:

  • JIRA

  • Visual Studio Code, Vim

  • Microsoft Excel/PowerPoint and Google Sheets/Slides

Website analytics and user behaviour:

  • Google Analytics

  • Google Search Console

Operating systems:

  • 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:

  • Presentation of the results from the measurement performed by the students using ATLAS data

  • Discussion of the presented results

  • Session of Q&A (questions and answers about particle physics, life at CERN, etc)

  • 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.