Turning AI into real-world systems • Deep Learning • Cloud ML (GCP, Azure, IBM) • Algorithmic Trading
I am a Machine Learning Engineer and Data Scientist with a background in Physics and more than 6 years of experience in algorithmic Forex trading, risk management, and AI automation.
- I build MQL5-based trading bots with advanced strategies, robust risk controls, and real-time analytics.
- I work across the full ML lifecycle data collection, preprocessing, feature engineering, model development, deployment, and monitoring.
- Experienced with cloud ML platforms (GCP, Azure, IBM Cloud) and production ML pipelines.
- Passionate about time series forecasting, deep learning, NLP, and recommender systems.
- My mission: turning AI into production-ready systems that deliver measurable business impact.
Programming & Tools
Python • SQL • Git • REST APIs • Jupyter • Docker
Machine Learning & AI
Scikit-learn • XGBoost • PyTorch • TensorFlow • Keras • MLOps
Deep Learning
CNNs • LSTMs/RNNs • Transformers • Reinforcement Learning • Generative AI
Cloud & Data Engineering
Google Cloud • Microsoft Azure • IBM Cloud • Data Pipelines • Big Data Tools
Finance & Quant MQL5 • Algorithmic Trading • Risk Management • Time Series Forecasting • Quantitative Modeling
Visualization & Communication
Matplotlib • Seaborn • Power BI • Data Storytelling • Technical Communication
- IBM: Data Science, Machine Learning, Deep Learning & RL, Generative AI, SQL & Databases, Data Visualization
- Microsoft: Azure Machine Learning, Foundations of AI & ML
- Google Cloud: How Google Does ML, Production ML Systems
- DeepLearning.AI: Supervised ML: Regression & Classification
- University of Washington: Machine Learning Foundations
- Finance Specializations: Portfolio Construction (EDHEC), Trading ML & GCP (NYIF), Python & Statistics for Finance (HKUST)
Full list available on LinkedIn
Here are some of my best open-source projects:
- Stock-LSTM-Forecasting — End-to-end LSTM pipeline for time-series forecasting with reproducible metrics and plots.
- Image-Captioning-CNN-LSTM — CNN encoder + LSTM decoder to generate captions, with BLEU evaluation.
- Sentiment-Analysis-BERT — Fine-tuned BERT model for text sentiment analysis with evaluation and visualizations.
- Sales-Data-Analysis — Exploratory analysis and insights from sales datasets.
- Demand-Forecasting — Predicting product demand with ML models for retail & e-commerce.
- Movie-Recommendation-System — Personalized recommender system using collaborative and content-based filtering.
“AI is not just about models, it’s about systems that create measurable impact.”