About Luis Alejandro
Data scientist with a PhD in particle physics and industrial experience. During my over 10 years experience of public research career I have been member of three big international collaborations. In this semi-corporate framework, I supervised research teams for exploiting the experiment’s data as well as for instrumental operations and R&D. Several years ago I decided to move to the private sector in the domain of Data Science to deepen my skills in machine learning and AI. During the last few years I got involved in the innovative world of start-ups, working as lead applied researcher. I being involved in projects going from fraud detection in e-commerce to content understanding in social media. Currently, I am looking for new opportunities to exploit my expertise in building AI-applications in a multidisciplinary and international environment to continue developing my career.
Spanish
Native or bilingual
English
Fluent
Italian
Fluent
French
Fluent
Can work on-site
Strasbourg (up to 50km)
Experience
- AaquaSenior Applied ResearcherJanuary 2021 - October 2022 (1 year and 9 months)Strasbourg, FranceAaqua was a social media company with the goal of revolutionizing the industry by allowing people to join passion communities and be in direct contact with brands and companies involved in such passions (e.g., music, sports, fashion, ...). I was part of the AI-CORE team as one of the leads applied researchers. This team was a center of ML and AI expertice providing a service any BU requiring AI-based solutioning for their use-cases. My role:- I was a founder member of the team. I significantly contributed to build the team by: candidate screening, tech-tests creation, candidates interviewing and assessment.- Built a team of 5 applied researches and 2 MLOps engineers- I led the R&D activities for several use-cases, and coordinated with engineering for protyping and production deployment Projects:- Assessment of 3rd party AI model for content moderation (Amazon, Perspective, Spectrum Labs). I coordiated the data collection strategies, metrics evaluation, and model integration- Scalable solution for images/videos near-duplicates retrieval using SOTA AI embedding models (e.g. CLIP) and vector databases (VESPA)- Understanding communities and their interactions through association rules, topic modeling and graph algorithms
- Enygma SASLead Data ScientistFebruary 2019 - March 2020 (1 year and 1 month)Strasbourg, FranceEmygma SAS is a start up building a framework for fraud detection at large, initially concentrating in credit card online payments. My role- Lead data scientist- Team leader: interns and company's engineers- Architecture conception- Exploration data analysis and feature engineering- Model training with deeply unbalanced data:
- Classical classification algorithms.
- Multivariate-time-series classification.
- Collaboration with academia- Internships from master CSMI-UNISTRA (2 interns M1 and currently 1 intern M2)
- Internships from ECAM Strasbourg-Europe (2 interns in 2019, and one expected for 2020)
- Collaboration for R&D activities with the institute IRIMAS - Université Haut Alsace (UHA) Achievements
- Modular / configurable tool for model training and deployment into production- Deployment for an e-commerce client - PivigoData Scientist, S2DS Fellow (https://www.credential.net/mu6qzjkc)October 2018 - November 2018 (1 month)London, UKFive-week intense project in Data Science consulting for the UK Food Standard Agency (FSA, https://www.food.gov.uk/). The project consisted in using social media data to understand law enforcement issues related to allergen enquiries in restaurants, allergen labelling in food and allergic reactions self-reporting. The project included the use of Natural Language Processing techniques to select social medial post related to the issues mentioned above. The final deliverables to the FSA included:- A detailed report describing the results of analyzing 2 years of data collection.- A well documented analysis tool implemented in R language to analyze future data.- A dashboard for data exploration of allergen related issues in the different UK districts.
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Education
- Doctor of PhilosophyUniversité Paris Diderot2008PhD in Physics, Particle Physics
- Master in Physics, PhysicsUniversidad de los Andes (VE)2005Master in Physics, Physics
Certifications
- Virtual Program Science to Data Science (S2DS)Pivigo2018
- Deep Learning SpecializationCoursera2020