Carlos Zorita
Natural Language Processing Engineer
Madrid, Community of Madrid, Spain
Summary
👤
Senior🎓
Top SchoolCarlos Zorita is a Natural Language Processing engineer and computational linguist with a PhD in Linguistics and 11 years of hands-on experience building NLP systems across academia and industry. He has a proven track record designing language-processing pipelines, information extraction, polarity annotation, and conversational agents, and currently applies linguistic methods to combat money laundering at Lynx Tech. His background spans Spanish, Japanese and English NLP—developing taggers, lexicons and domain-specific extractors—and includes leadership of NLP teams and client-facing solution design. Comfortable moving projects from research prototypes to production, he blends deep theoretical knowledge with pragmatic software engineering. Outside work he’s a self-described cat lover, hinting at a detail-oriented but personable approach to complex language problems.
11 years of coding experience
4 years of employment as a software developer
PhD in Linguistics Spanish and Japanese NLP Corpus Linguistics, PhD in Linguistics Spanish and Japanese NLP Corpus Linguistics at Universidad Autónoma de MadridBachelor of Arts - BA English Language and Literature General, Bachelor of Arts - BA English Language and Literature General at Universidad de Alcalá
Spanish, English, Japanese
Github Skills (13)
gaussian8
k-means-clustering8
feature-extraction7
stochastic-processes6
kmeans6
self-organizing-map6
classification6
gaussian-processes5
probabilistic-models5
clustering-algorithm5
python5
machine-learning4
clustering4
Programming languages (2)
Github contributions (5)
cvillacampa/GPInputNoise
Jun 2020 - Dec 2020
Multi-class Gaussian Process Classification with Noisy Inputs
Contributions:25 commits, 5 PRs, 21 pushes in 5 months
pythonfeature-extractionmachine-learninggaussianprobabilistic-models
Morcu/q-means
May 2019 - May 2019
Quantic implementation of the k-means clustering algorithm
Contributions:25 commits, 2 PRs, 17 pushes in 1 day
k-means-clusteringk-meansmachine-learningclusteringmeans
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