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Francisco Rodriguez

Senior Machine Learning
Habilidades
(Autoevaluación)
Machine learning 100%
Python 100%
Data lake 100%
No sql 100%
Data science 80%
JavaScript 80%
Postgresql 80%
Node.js 80%
Deep learning 80%
Database sql 75%
Idiomas
English:
  • Speaking
    70%
  • Reading
    70%
  • Writing
    70%
Perfil profesional

I am a Senior Data Scientist with a background in Software Engineering. I am currently creating for an important fintech in the US all the data engineering and infrastructure of Mlops to implement card fraud models. In my role at Startup Dondo, I helped

Experiencia laboral

Senior Machine Learning
onikom | Abril 2022 - Actualmente (4 years 7 months)
Habilidades utilizadas

Lead the creation of the MLOPS of a fintech project for the detection of fraud in the use of credit cards. Work in the role of data engineer integrating the entire data pipeline for the management and integration of information sources. I worked in the data science role creating doing all the feature engineering. I worked in the machine learning area creating the fraud prediction models and in the creation of the machine learning pipeline

Senior Ai Engineer
dondo | Enero 2021 - Marzo 2022 (1 year 2 months)
Habilidades utilizadas

Dondo is a leading goods and services marketplace in Colombia whose mobile app is #3 in the Google Play store. Developed, deployed, and refined a custom machine learning recommender system using collaborative filtering, factorization matrices and neural nets that led to a 26% improvement in conversion rates. Oversaw the ground-up implementation of MLOps infrastructure using Microsoft Azure's Synapse Analytics, Machine Learning, Data Bricks, and K

Cto
link desing | Enero 2012 - Enero 2021 (9 years)
Habilidades utilizadas

Link Design is a software development firm that specializes in building secure machine learning applications for clients in the insurance, finance, and telecommunication industries. Supervised the development of an interoperable artificial intelligence system comprising of predictive models, neural networks, and intelligent agents for a collections service; its implementation ultimately improved the weekly collection rate by 200%.. Designed, prot

Formación académica
Computer Science
Universidad de las fuerzas armadas (espe) | Master
Generado por

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