Data Analyst | Finance & AI Enthusiast
Developed a grounded AI and analytics capstone project using ball-by-ball cricket data across Test, ODI, and T20 formats. Built a Flask-based web application powered by a large language model to provide interactive, data-driven cricket insights. Conducted exploratory data analysis, created performance metrics, and implemented a chatbot interface to deliver accurate contextual responses to user queries. Focused on presenting complex statistical information clearly and effectively for non-technical users.
View on GitHubBuilt a full-stack automated trading system with live portfolio monitoring and strategy visualisation. Implemented a Flask web app to execute trades via the Alpaca API, with yFinance as a fallback. Integrated AWS S3 for caching data and logs, and scheduled background tasks with APScheduler. Developed interactive Plotly charts to track portfolio performance against the S&P 500 (SPY), implemented dynamic allocation algorithms based on analyst target prices, and deployed the application to Heroku.
Live DemoCompleted a group project as part of the Digital Futures programme, analysing simulated company data to identify revenue growth drivers, customer acquisition trends, and geographic expansion opportunities. Applied Python and Tableau for data cleaning, exploration, and visualization. Developed actionable insights for non-technical stakeholders and delivered a presentation summarising findings and recommendations. Focused on combining quantitative analysis with clear business storytelling.
View on GitHubConducted a solo data-driven project analysing over 5,000 films to explore the relationship between budget, revenue, genre, and profitability. Used Python for data cleaning, statistical analysis, and visualisation, creating metrics to identify trends and patterns driving box-office success. Built interactive charts to communicate findings and provided insight into factors separating blockbuster hits from financial misfires.
View on GitHubA data-driven project analysing customer churn for Swan Teleco. Conducted a full workflow: data cleaning, exploratory analysis, and predictive modelling using Random Forest, Logistic Regression, and SVM. Generated churn probability scores, identified the top 500 at-risk customers, and provided actionable insights to improve retention, such as targeted incentives and improved onboarding. Achieved 85.5% ROC AUC with the Random Forest model.
View on GitHubAnalysed global health and socioeconomic factors influencing life expectancy (2000–2015) using WHO data. Built a complete data science pipeline: exploratory data analysis, feature engineering, and predictive modelling with linear regression. Deployed a live web interface allowing users to predict life expectancy using either an advanced or simplified model while maintaining ethical and privacy-conscious design.
View on GitHub Live DemoCo‑founded and moderated a 2,500+ member Discord server for University of Southampton students — implemented moderation bots, hosted virtual events, and supported community engagement throughout the COVID‑19 period.
Python, JavaScript, SQL, Flask, GitHub, Heroku, AWS S3, Tableau
Pandas, NumPy, Plotly, Alpaca API, Alpha Vantage, Discord API
Visualization, statistical modeling, scientific computing
Web development, API integration, automation, deployment
LLMs, Problem solving, mathematics, community building, event planning, remote collaboration