My Portfolio:
Showcasing My Data Science Skills
Each project has been carefully selected to showcase my skills across the entire spectrum of Data Science - from simple to complex methodologies, allowing me to show how I can dive into the detail and uncover insights.
Projects include; linear regression, clustering, classification, supervised and unsupervised learning, applying neural networks and deep learning working with structured and unstructured data.
Feel free to browse through my projects and witness the transformative power of data science in action!
💼 A 6-Week Employer Project Completed as Part of a Team: Analysing Quarterly Results of G-SIBs with Advanced Language Models
🧠 RAG | Sentiment Analysis | Topic Modelling | NLP | LLMs & SLMs
This project aimed to enhance the Bank of England and Prudential Regulation Authority's risk assessments by applying advanced language models to analyse quarterly earnings call transcripts from financial institutions. This approach helps proactively assess firms' stability, identify high-risk behavior, and improve oversight, potentially preventing future financial crises.
A project in partnership with the Bank of England through the University of Cambridge, where I served as the Data Science Team Lead.
🛍️ 12 hr Project: Customer Segmentation with Clustering
🔍 Data-Driven Insights for Retail Success | K-means Clustering | Elbow Method | Silhouette Score
This project applies critical thinking and machine learning to design clustering models for segmenting customers driving smarter marketing strategies to improve customer experiences.
🚢 12hr Project: Detecting Anomalous Ship Engine Activity
🛠️ Unsupervised Anomaly Detection | No Ground Truth | SVM | Isolation Forest
This project tackles the challenge of detecting anomalies to ensure optimal engine performance by applying statistical and ML-based anomaly detection approaches.
📚 36hr Project: Book Sales Forecasting with Time Series and Machine Learning
📈 Sales Prediction | Time Series Analysis | ARIMA | XGBoost | LSTM | ACF, PACF, Ljung-Box |
This project utilizes time series data and advanced ML models to forecast book sales, enabling data-driven decisions on inventory and marketing strategies.
🎓 12hr Project: Predicting Student Dropout with Advanced Machine Learning
🧠 | Supervised Learning | XGBoost | Neural Networks
In this project, I used advanced supervised learning techniques to predict student dropouts, aiming to reduce high dropout rates that can negatively impact an institution’s finances, reputation, and student satisfaction.
Due to confidentiality reasons I cannot show the original data or graphical output, instead only the code and general, anonymised summaries are kept.
🎓 19hr Project: Topic Modelling with NLP in a Real-World Context
🧠 | NLP | BERTopic | Topic Modelling |Emotion Analysis
In this project, I applied advanced NLP techniques, including BERTopic and emotion analysis, to uncover themes in customer reviews, helping a gym chain enhance its customer experience.
Due to confidentiality reasons I cannot show the original data or graphical output, instead only the code and general, anonymised summaries are kept.