Как вы себя чувствуете в самоизоляции, как адаптируетесь, как работаете, какими привычками обзаводитесь — об этом наш новый опрос. Пройдите его (займёт 10 минут) и в конце узнайте, как дела у других.
Профессиональные навыки
GitPythonJavaDockerBashSQLLinuxDjangoRestful apiFlask
Опыт работы
Dextra (Brazil)
Python Developer
Ноябрь 2019 — По настоящее время (6 месяцев)

I participated in two projects. The first involving the largest credit analysis company in Latin America with elements of big data. And the second with the largest television broadcaster in Latin America, involving migration between data and content between servers. All using Python as the main language

- Serasa Experian project using Big Data tools like pySpark and Hadoop to check the score, based on previously trained neural network models

- Globo.com project project using Python (web scraper + Flask + Django) for data communication between platforms

GPr Systems (Brazil)
Python Developer
Июнь 2019 — Ноябрь 2019 (6 месяцев)

(Networking monitoring position using Python and Linux)

- Use of SNMP protocol for network monitoring. Itaúmon project of Itaú Bank (biggest bank in Brasil) to monitor and control all active points of the network using multi-thread discovering.

- Web development with Django and javascript applications.

- Creation of Machine Learning algorithms to detect fraud and network attacks.

- Implementation of multiple Docker containers in micro services.

Python Developer
Март 2019 — Июнь 2019 (4 месяца)

- Creation of convolutional neural networks models for forest fire detection. Networks made using OpenCV for initial frame filtering and Keras classification (Tensorflow backend).

- Use of Flask and FastAPI to create fire detection APIs. Solution integrated in the modules of customer monitoring cameras.

- Management of trainee learning activities.

Февраль 2016 — Январь 2019 (3 года)

● Preventive basic penetration tests in internal web applications and server services

exposed on the internet.

● Development in Java (object oriented) back end. Integration of machine learning services

with legacy structure.

● Development in Python related to the capture of images by monitoring cameras with the

use of machine learning with the Tensorflow (Google) and OpenCV (NVIDIA) libraries for

recognition and detection of objects in images and video streams.

● Choice of features and configuration of neural networks using the scikit-learn library to

classification and regression of data behaviors using previous information collected.

● Use of Python and Shell Script to optimize access to client servers and

irregularities in services