Hadi Ahmed
Data Scientist @ Mastercard
About Me
I'm a Data Scientist at Mastercard working on machine learning and analytics for the UK payment infrastructure. I studied Mathematics and Computer Science at Durham University, where I developed a strong foundation in statistical modelling and algorithmic thinking.
I enjoy tackling challenging problems at the intersection of data, technology, and real-world impact - whether that's classifying millions of payment transactions, building Bayesian models for sports prediction, or developing real-time fraud detection systems. This portfolio showcases some of the projects and ideas I've been working on.
Featured Projects
Real-Time Fraud Detection
A machine learning system that detects fraudulent credit card transactions in real-time using streaming data and advanced ML models. Features live visualisation and monitoring dashboard.
Bayesian Football Predictor
A probabilistic prediction system using Bayesian inference to forecast Premier League match outcomes. Features uncertainty quantification, expected goals distributions, and most likely scorelines.
Professional Experience
Data Scientist @ Mastercard
Vocalink (UK Payment Systems)
Working on machine learning and data science projects supporting the UK payment infrastructure. My work spans semi-supervised learning, forecasting, and large-scale payment analytics - helping process over 500 million transactions monthly and partnering with organisations like the ONS on economic measurement.
Key Projects
Major initiatives I've worked on at Mastercard
Payment Purpose Classification
Built semi-supervised ML models to classify 500M+ monthly UK BACS payments by economic purpose. Engineered temporal features across billions of transaction records to understand payment intent and enable downstream analytics for banks and regulators.
Industry Flow Analysis (ONS Partnership)
Partnered with the Office for National Statistics to model £400bn+ in monthly inter-industry payment flows. Applied unsupervised learning to classify accounts by industry sector, enabling government economists to track money movement across the UK economy.
Forecasting & Reporting Infrastructure
Developed interactive Power BI dashboards with embedded forecasting models for Pay.UK and major UK banks. Built end-to-end MLOps pipelines using Python, SQL, and Jenkins for automated model retraining, monitoring, and deployment - reducing manual intervention and production risk.
Payments Innovation Research
Led internal initiative researching tokenised account-to-account payment innovations (RLN, GBTD). Developed strategy presentations translating complex technical concepts into commercial opportunities, presenting to executives and shaping company thinking on future payment rails.
Education
BSc Mathematics & Computer Science
Durham University
2:1 (Upper Second Class Honours)
Key modules: Decision Theory, Machine Learning & Neural Networks, Data Science & Statistical Computing, Algorithmic Game Theory
A Levels
Drayton Manor High School, Ealing
A*A*A* in Mathematics, Further Mathematics, and Physics - highest result in school year
Skills & Technologies
Machine Learning
Scikit-learn, XGBoost, Bayesian Modelling
Python
Pandas, NumPy, SciPy
Time Series
Forecasting, Feature Engineering
SQL & Data Engineering
PL/SQL, ETL, CDC
MLOps & Deployment
Docker, MLflow, Kafka, Jenkins CI/CD
Web & APIs
FastAPI, React, Next.js