Schlagwörter
Predictive Modelling
Statistiken
Python
Datenverarbeitung
Software Version Control
Programming Languages
Java
Automatisierter Handel
Bash Shell
Big Data
Ubuntu
Information Engineering
Statistische Hypothesentests
Machine Learning
Monte-Carlo-Simulation
Numpy
Handel
Streaming
Integration (Software)
Data Science
Jupyter
Git
Pandas
Matplotlib
Scikit-learn
Daten-Pipeline
Fedora
Unsupervised Learning
+ 18 weitere Schlagwörter anzeigen
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Julian-Bonitz-CV_090525.pdf
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Skills
Python Programming
Strong proficiency in Python for developing and deploying predictive models in a high-performance trading environment.
Statistical Analysis
Solid foundation in statistics, applying concepts like statistical inference and Monte Carlo simulations in data science projects.
Machine Learning
Experience with supervised and unsupervised learning techniques, model evaluation, and hypothesis testing for predictive modeling.
Programming Languages
Proficiency in multiple programming languages including Bash, R, Julia, Java, and C, with varying levels of expertise.
Data Processing Tools
Familiarity with libraries and tools such as Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn, and Gspread for data manipulation and analysis.
Version Control and Development Environments
Experience with Git for version control, and platforms like Ubuntu Linux, Fedora Asahi Remix, Jupyter Notebooks, and VS Code for development.
Data Engineering
Skills in building scalable data pipelines, integrating live data streams, and working with large datasets in real-time environments.
Projekthistorie
Designed and evaluated predictive models for real-time market data analysis, integrated live data streams, developed algorithmic trading strategies, and worked in a proprietary environment under strict NDA.