Piotr Kapelusiak

I am transitioning from a strong finance background (Fund Accounting, Financial Reporting, UCITS/AIFM) into AI Engineering and Quantitative Development.

I build data-driven systems, trading strategies, and machine learning models focused on financial markets and automation.

Currently focused on Python, machine learning, and real-world AI applications in fintech.

Background in Fund Accounting and Financial Reporting within banking and investment environments. Experience with NAV calculations, reconciliations, regulatory reporting (UCITS/AIFM), and financial data analysis.

Currently applying this knowledge to AI and quantitative finance projects.

Trading Bot (Python)

Algorithmic trading strategy using EMA, VWAP, and AI-based filtering. Includes backtesting, performance metrics (Sharpe Ratio, Max Drawdown), and portfolio simulation.

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Quantitative Strategy

Data analysis and backtesting framework for financial strategies. Focus on risk management, statistical metrics, and optimization.

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AI Market Prediction Model

Machine learning model for financial time series prediction. Uses Python, data preprocessing, and model evaluation techniques.

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Python | Machine Learning | Data Analysis | Trading Systems | Financial Markets | APIs | Backtesting | SQL | Git

Email: piotr.kapelusiak@gmail.com

GitHub: github.com/piotr9912

LinkedIn: https://www.linkedin.com/in/piotr-k-772a0126b/

Kaggle: https://www.kaggle.com/piotrkapelusiak