Florencia聽Montero
Country Manager at Fintual
Santiago, Santiago Metropolitan Region, Chile
Summary
馃懁
Senior馃帗
Top SchoolFlorencia Montero is a technology leader and software engineer with 11 years of experience who currently serves as Country Manager at Fintual after progressing from a full-stack developer role there. She holds an MEng in Computer Science and has a background in computational science, combining rigorous academic training with hands-on product delivery under the Shape Up methodology. Her work spans back-end, databases and responsive front-ends, and she has led interdisciplinary research applying BERT to detect incivility in Chilean news forums and map conversation networks. Florencia has substantial teaching and coaching experience at Pontificia Universidad Cat贸lica de Chile, where she coordinated courses, managed capstone projects, and mentored student teams. She brings entrepreneurial experience as a co-founder and practical delivery chops from internships and product roles, making her comfortable at the intersection of data-driven research, software engineering and people leadership. An unusual strength is her ability to translate academic NLP research into actionable insights for product and community engagement.
11 years of coding experience
8 years of employment as a software developer
6.9, 6.9 at St. Margaret's British SchoolMaster of Engineering - MEng, Computer Science, 6,6, Master of Engineering - MEng, Computer Science, 6,6 at Pontificia Universidad Cat贸lica de ChileIB Diploma, 35, IB Diploma, 35 at International Baccalaureate
Spanish, English
Github Skills (29)
del10
distilbert8
csharp7
korean-nlp6
css6
classification6
nlp5
question-answering5
javascript5
pytorch4
machine-learning4
text-classification4
deep-learning4
natural-language-processing4
bert3
Programming languages (4)
Github contributions (5)
flobarrios/basic-comments-app
Sep 2018 - Jan 2021
Contributions:2 PRs, 9 pushes, 3 branches in 2 years 5 months
flobarrios/simpletransformers
Dec 2019 - Jun 2020
Transformers made simple with training, evaluation, and prediction possible with one line each. Currently supports Sequence Classification (binary, multiclass, multilabel), Token Classification (NER), and Question Answering. Built on top of the Hugging Face Transformer library.
Contributions:4 pushes in 6 months
sequencedistilbertberttrainingmulticlass
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