CV

Education

• Docteur en Informatique, Université du Luxembourg, 2020
• Licenciado en Ciencias de la Computación, Universidad de Buenos Aires, 2016
• Analista Universitario en Computación, Universidad de Buenos Aires, 2013

Work experience

• Applied Scientist II at Amazon / AWS, Berlin, October 2022 - Present.
  • Applied Scientist on AWS teams (incident prevention & response, then fraud prevention), owning ML and production systems from design through operation.
  • AWS Fraud Prevention (mid-April 2025 - Present): Owned a production pipeline for copyright-abuse / illegal-streaming claims against AWS resources (ingestion, account/resource attribution, investigation workflows); stabilized the service under a large traffic increase and migrated it onto a standardized orchestration platform; built a GenAI proof of concept that drafts operational-readiness answers from technical documentation (reasoning, citations, evaluation against historical reviews); delivered production migrations and reliability work; participated in on-call.
  • Incident prevention & response ML (October 2022 - mid-April 2025): Designed, built, and operated a time-series metrics platform for incident-response ML (ingest, Parquet storage, Athena/Glue querying, data-quality and metric-drift monitors, client libraries), scaling from hundreds to tens of thousands of metrics; led LLM-based automatic tagging of semi-structured post-incident writeups for availability and change-safety programs; modernized a production outage-detection stack and refactored a metric diagnosis service; mentored teammates and supported hiring.
• Postdoctoral Researcher at LIST, October 2020 - September 2022.
  • MODALES Project: Responsible for the development and deployment of a mobile app that collects information from the device sensors and from the vehicle on-board diagnosis (OBD). The goal of the application is to offer recommendations to correct the driver behavior towards the reduction of vehicle emissions. I developed the app in Flutter, using also Kotlin and Swift, and it includes an implementation of the ELM327 protocol for communicating with the CAN bus through OBD dongles. I was also responsible for the development of a REST API, the database administration and the integration with external services. I also participated in weekly meetings with the project consortium and contributed in the writing of project deliverables and research publications.
  • 5G-EMIT Project: Contributed in the writing of project deliverables and research publications related to the assessment of 5G EMF emissions.
  • 5G-PLANET Project: Responsible of a platooning demo involving small robot cars and deep learning.
• Ph.D. Student at SnT, University of Luxembourg, October 2016 - October 2020.
  • Research on deep generative models for tabular / mixed categorical–numerical data (oversampling, imputation) and machine learning for suspicious activity in banking and blockchain; grant-backed industry collaboration.
  • Built an anomaly-ranking prototype for an industrial partner and large-scale data collection/processing pipelines; thesis: Machine Learning Techniques for Suspicious Transaction Detection and Analysis.
• Research & Development Engineer at Avature, April 2015 - September 2016.
  • Developed and maintained a resume parsing tool using natural language processing and machine learning.
  • Interacted with other teams, analyzing their data and developing information retrieval tools.
• Research & Development Engineer at Invgate, March 2013 - February 2015.
  • Researched, designed and developed a new product prototype involving network discovery tools, configuration management and risk analytics; mentored one engineer while coding as an individual contributor.
• Game Developer at Bad Juju Games, January 2012 - February 2013.
  • Developed mobile video games using Unity3D and internal development tools.
• Game Developer at Metrogames, January 2009 - December 2011.
  • Developed Flash mini-games for social platforms.
  • Designed and developed an on-line multiplayer poker game for social platforms as an individual contributor; mentored one teammate.
• Mobile & Web Services Developer at Sondeos, June 2008 - January 2009.
  • Developed and designed prototype Blackberry applications and their server counterparts.
• Web Developer at Sauriobee, June 2007 - June 2008.
  • Developed websites with dynamic contents and managed small databases.
• Junior Web Developer at U75, August 2005 - June 2007.
  • Developed Flash websites and ads.

Training

• Kaggle Micro-Courses, 2020.
• Second Data Science Summer School (DS3) at École Polytechnique, June 2018.
• Deep Learning Specialization at Coursera with Andrew Ng, February 2018.
• International Summer School on Deep Learning 2017 at Universidad de Deusto, July 2017.
• 3rd International Winter School on Big Data at Università degli Studi di Bari, February 2017.
• Escuela de Ciencias Informáticas (ECI) (winter school) at UBA, July 2014, 2015 and 2016.
• Machine Learning at Coursera with Andrew Ng, December 2013.

Skills

• Programming Languages:
  • Preferred: Python.
  • Moderate Experience: Java, PHP, Javascript, HTML, CSS.
  • University projects: C, C++, C#, objective-c, Haskell, Smalltalk, R, MATLAB, Octave, Scala, Lua.
• Machine Learning, Deep Learning, Data Science:
  • pytorch
  • tensorflow
  • keras
  • numpy
  • scikit-learn
  • pandas
  • matplotlib
  • jupyter
  • Weka
• Natural Language Processing, Scrapping & Parsing:
  • NLTK
  • Gensim
  • Stanford CoreNLP
  • Scrapy
  • spaCy
  • ply
  • lex
  • yacc
• Cloud & Production (AWS):
  • Amazon Bedrock
  • AWS CDK
  • Lambda
  • S3
  • Glue
  • Athena
  • DynamoDB
  • SQS / SNS
  • CloudWatch
• Game development:
  • Flash
  • Unity3D
  • Godot
• Web development:
  • jQuery
  • AngularJS
  • Twitter Bootstrap
  • Flask
• General Development
  • OOP
  • design patterns
  • basic database knowledge
  • development processes
  • version control
• Languages
  • Spanish: native
  • English: fluent
  • French: medium level
  • Italian: beginner
  • Luxembourgish: beginner