Franco De Giovannini
Score: 0 pts
Data Scientist
Join Competition
Experience & Education
Tengo entre 1-2 años de experiencia
Licenciatura o equivalente
Tengo un título o calificación formal en data science o un campo relacionado (matemáticas, ciencia, ingeniería, ciencia de la computación)
I studied Economics at the Catholic University of Cuyo. I've been working with the python data science ecosystem for the last three years. Last year I took a 200 hours Data Science course at Digital House, and got a recommendation to apply for a teaching position at the institution. I've been working as the Data Scientist since October 2019 at a small software consultancy company located in Buenos Aires. I lead a team of 4 developers, with different backgrounds in order to deploy our ML solutions into production.
We've developed two main solutions: the first one analyzes scanned legal documents and extracts names, dates, and other relevant entities. The other extracts information from scanned financial reports. Both solutions were developed for financial and banking institutions, with the aim to reduce the processing time when acquiring new clients.
You can find a demo of the former here:
http://l01.leafnoise.io:39001/jobs
Score: 0 pts
Data Scientist
Data Scientist
Join Competition
Experience & Education
Tengo entre 1-2 años de experiencia
Licenciatura o equivalente
Tengo un título o calificación formal en data science o un campo relacionado (matemáticas, ciencia, ingeniería, ciencia de la computación)
I studied Economics at the Catholic University of Cuyo. I've been working with the python data science ecosystem for the last three years. Last year I took a 200 hours Data Science course at Digital House, and got a recommendation to apply for a teaching position at the institution. I've been working as the Data Scientist since October 2019 at a small software consultancy company located in Buenos Aires. I lead a team of 4 developers, with different backgrounds in order to deploy our ML solutions into production.
We've developed two main solutions: the first one analyzes scanned legal documents and extracts names, dates, and other relevant entities. The other extracts information from scanned financial reports. Both solutions were developed for financial and banking institutions, with the aim to reduce the processing time when acquiring new clients.
You can find a demo of the former here:
http://l01.leafnoise.io:39001/jobs
