Python Developer
Overview
Short Summary
The candidate is a Python/Django developer with experience in web application development and data manipulation. He has worked as a Python programmer, focusing on data manipulation and visualization, and as a software test engineer, creating automated tests. He has a strong knowledge of programming languages such as C, Java, and Python, as well as experience with PostgreSQL and Microsoft Office. He is proficient in English and has basic knowledge of German. Additionally, he has experience with parallel programming, object-oriented programming, and machine learning. He is also familiar with Docker containerization and software modeling with Enterprise Architect.
Work Experience
October 2021 - Present: Python/Django Developer - Development of a web application for a foreign client using Python (Django) for the backend and Vue.js for the frontend
September 2020 - Present: Python Programmer - Data manipulation (Pandas, NumPy), visualization creation (Highcharts.js), code optimization (profiling, multiprocessing), and CI/CD pipeline modification (YAML) in the field of financial analysis and investment strategies
June 2019 - September 2020: Software Test Engineer - Creation of automated tests in Python, maintenance of existing testing scripts in the telecommunications and video streaming (MPEG) domain
2016 - 2019: Bachelor's Degree in Informatics from the Faculty of Informatics and Information Technologies at the Slovak Technical University in Bratislava
2008 - 2016: Gymnasium B.S. Timravy in Lucenec, Slovakia
Skills: Advanced in C, Java, PostgreSQL, Python, Microsoft Office, Adobe Photoshop. Basic knowledge in Git, Elasticsearch, Linux, Docker, TensorFlow, and scikit-learn
Languages: Intermediate level in English (B2), Beginner level in German (A2)
Additional information: Experience in parallel programming and pointer arithmetic in C, OOP principles, design patterns, GUI development with JavaFX, JDBC with PostgreSQL, Flask for backend development in Python, basic knowledge of data science and machine learning (neural networks, Keras, regression and classification models, scikit-learn), working with NoSQL databases, Elasticsearch, visualization in Kibana, software modeling with Enterprise Architect, and Docker containerization
