My Expertise
I’m a machine learning specialist with 3+ years of experience building real-time data systems across healthcare, gaming, and commercial analytics. My background combines hands-on technical work with research experience, including an MSc in AI from the University of St Andrews where I specialized in computer vision.
Featured Projects
A selection of my recent work
Skills
Technologies and tools I work with
Languages
My main programming languages are Python, Java, Julia, SQL and web-based languages. I also have experience programming in Go, Bash, Haskell, MATLAB, and R.
Frameworks
I have worked with a variety of ML focused tools such as Scikit-Learn, Pandas, LightGBM, XGBoost, NumPy, Matplotlib, Keras/Tensorflow, PyTorch, Plotly, OpenCV, NLTK, and general web frameworks such as Astro, React, Django, Flask, D3.js.
Tools
A few of the tools that I have used on a daily basis include LLMs, JetBrains IDEs (PyCharm,IntelliJ IDEA), JupyterLab, git (GitHub, BitBucket), Vim, Vercel, and different OS (macOS, Ubuntu, ArchLinux, Debian).
Education
MSc Artificial Intelligence & Computer Science at University of St Andrews
A research-led postgraduate degree with a strong focus on machine learning, computer vision, NLP, logic programming, and statistical analysis. Emphasis on applied deep learning, model evaluation, and real-world impact through interdisciplinary projects.
- Dissertation: Investigated Single-Shot Object Detection (YOLO) on aerial imagery to automate seal population counting for conservation research
- Gained practical experience in TensorFlow, OpenCV, CNNs, and dataset curation for real-world object detection
BSc(Hons) Software Engineering at University of Malta
A Bachelor's degree emphasizing core computer science principles and full-cycle software engineering — from systems design to implementation and testing.
- Covered topics in software architecture, intelligent systems, and algorithmic design
Work Experience
Data Scientist at Gambling.com Group
Focused on improving click-through rate (CTR) forecasting to optimize affiliate offer rankings and monetization strategies in the online gambling sector.
- Developed and refined CTR prediction models to prioritize affiliate offers across multiple gambling platforms.
- Collaborated with marketing and product teams to integrate forecasted CTR scores into deal ranking logic.
- Performed exploratory analysis to identify behavioral patterns and seasonality in user engagement data.
- Initiated improvements to model evaluation pipelines.
- Conducted exploratory data analysis (EDA) to evaluate performance trends across markets and identify high-potential regions for future entry.
Research Support Officer at TargetMI
Leveraging machine learning to uncover biomarkers for myocardial infarction using genomic and clinical data.
- Developed ML pipelines for structural variant analysis in genomic data, aiding in early MI detection.
- Built risk prediction algorithms using multimodal data (genetic, lifestyle, clinical) for MI stratification.
- Led subtype classification of myocardial infarction cases using domain-informed ML methods.
- Helped design RNA-Seq pipelines for high-throughput gene expression profiling.
Data Scientist at Gaming Innovation Group
Delivered predictive models and responsible gambling solutions in a high-volume customer analytics environment.
- Designed Bayesian models to optimize customer retention strategies.
- Built collaborative filtering models for personalized recommendations.
- Developed behavioral anomaly detection systems to promote responsible gambling.
- Set up reproducible ML experimentation using MLflow and Docker; improved model tracking and transparency.
- Presented key insights and model results to senior stakeholders across compliance and marketing.