Python developer (Real-time US stock evaluation system)
(Banken und Finanzdienstleistungen, 10-50 Mitarbeiter)
Schlagwörter
Skills
Hello,
please check the video link https://drive.google.com/file/d/1KXgrjDHHqxayluZqQM9DyWr3W8JK-V0Z (if the link is deleted here, then you can find the link in my CV). It is a presentation of one of my projects.
Python development using:
• GUI/frontend: PyQT, wxWidgets, Plotly Dash;
• backend: Docker, Python, SQLAlchemy/Alembic (PostgreSQL, SQLite, MariaDB), TensorFlow;
• data streaming: Apache Kafka;
• client-server communication: FastAPI, websockets;
• web scraping: Python Scrapy, BeautifulSoup;
• version control: GitHub, Bitbucket, Fork, Jira;
• python multiprocessing, multithreading and asynchronous programming.
please check the video link https://drive.google.com/file/d/1KXgrjDHHqxayluZqQM9DyWr3W8JK-V0Z (if the link is deleted here, then you can find the link in my CV). It is a presentation of one of my projects.
Python development using:
• GUI/frontend: PyQT, wxWidgets, Plotly Dash;
• backend: Docker, Python, SQLAlchemy/Alembic (PostgreSQL, SQLite, MariaDB), TensorFlow;
• data streaming: Apache Kafka;
• client-server communication: FastAPI, websockets;
• web scraping: Python Scrapy, BeautifulSoup;
• version control: GitHub, Bitbucket, Fork, Jira;
• python multiprocessing, multithreading and asynchronous programming.
Projekthistorie
01/2019
-
bis jetzt
Desing and impelemntation in Python real-time stock trading system, which should evaluate external stock real-time data, visualize and generate trading signals for broker APIs.
Data input: external data providers APIs (socket, Rest API).
Output for generated orders: broker API.
Backend: Python, PostgreSQL, Confluent/Apache Kafka.
GUI/frontend: PyQT, wxWidgets, Plotly Dash;
ML in Python: Pandas, Scikit-Learn;
Small video presentation of the project is here: -Hyperlink entfernt-
Data input: external data providers APIs (socket, Rest API).
Output for generated orders: broker API.
Backend: Python, PostgreSQL, Confluent/Apache Kafka.
GUI/frontend: PyQT, wxWidgets, Plotly Dash;
ML in Python: Pandas, Scikit-Learn;
Small video presentation of the project is here: -Hyperlink entfernt-
04/2022
-
06/2022
Python developer
(Transport und Logistik, >10.000 Mitarbeiter)
Migration of the existing system to FastAPI + SQLAlchemy/Alembic.
Backend db: MariaDB, sqlite.
Backend db: MariaDB, sqlite.
Zertifikate
Reisebereitschaft
In der Stadt Berlin mit einem Radius von 50 km verfügbar
Reisebereitschaft in Berlin und Umgebung. In anderen Fällen - remote.
Verfügbarkeit ab 1.11.2023, 40 Std./Woche
Verfügbarkeit ab 1.11.2023, 40 Std./Woche
