I can analyse big data, construct predictive models, and translate data into meaningful insights that drive business strategy.

Based in Glasgow, I am driven by a passion for developing innovative solutions to engineering challenges. I thrive on exploring new ideas, thinking creatively, and actively contributing to open-source projects. With a continuous pursuit of growth and learning, my long-term goal is to make a meaningful impact on both society and the environment.

⚙️ Founded Machine Learning Library Nalyst on 2022

pip install nalyst

pip install --upgrade nalyst

Experience in data analysis, preprocessing, and statistical methods, with a solid understanding of advanced mathematics. I'm familiar with build machine learning algorithms from scratch like regression, decision trees, random forest, SVM, and neural networks, as well as deep learning models such as CNNs, RNNs, and autoencoders. I’ve worked with clustering (hierarchical, DBSCAN), dimensionality reduction (PCA, SVD), and time series analysis. I can create dashboards and KPIs using Power BI and Tableau, and have experience in NLP, text mining, A/B testing, and deploying models, while maintaining data governance and quality.

Experience in technical and fundamental analysis, portfolio construction, and risk management. My expertise includes quantitative and trend analysis, start-up valuation, and in-depth equity and fixed-income analysis. I possess a strong understanding of alternative investments, option spread and pricing, and strategic financial planning. Involved in developing long and short term investment strategies, financial modelling, and forecasting, I excel in economic and market analysis, asset allocation, managing risk effectively and diversification. Additionally, I familiar with regulatory compliance and reporting practices.

• Programming Languages: Python, JavaScript, C++ and R Programming
• Web Development & Framework: HTML, CSS & Streamlit, Node.js, Django, React, and React Native
• Database: Microsoft SQL, SQL Lite, and Mongodb
• Data Visualisation Tools: Microsoft Excel, Power BI, Tableau, Matplotlib, and Seaborn
• Data Science Libraries (Api): Numpy, Pandas, Polars, statsmodels, Scikit-learn, Keras, TensorFlow, PyTorch, yfinance, pyttsx3, gTTS (Google Text-to-Speech), sounddevice, and SpeechRecognition
• Development Environments: Jupyter Notebook, Visual Studio Code, Anaconda, and Google Colab
• Microsoft Suite: MS Word, MS Excel, MS Visio, MS PowerPoint, and Google Analytics
• Collaborative Tools: Google Sheets, Google Doc, Google Drive, Dropbox, Discord, Zoom, MS Team, Monday.com and OneDrive.
• Graphic Design: Adobe Photoshop