CV
Education
- Ph.D. in Machine Learning, University of Sussex, 2017 – 2022
- Thesis: Fair Representations in the Data Domain
- Supervisor: Prof. Novi Quadrianto
- First year part-time, alongside a graduate role at American Express
- Built adversarial and normalising-flow models that learn fair representations which system designers and stakeholders can inspect
- B.Sc. (Hons) Computer Science, First Class, University of Sussex, 2013 – 2017
- Dissertation: Learning Using Privileged Information: A Unified Approach
- Faculty prizes for Outstanding Computer Science Student and Best AI Final Year Project
Work experience
- Oct 2026 – present: Senior Engineer (AI & Optimisation)
- Metasonixx Ltd
- Using AI and advanced optimisation techniques to produce novel acoustic metamaterial designs.
- Turning the team’s research into a reusable, reproducible and tested system built in Python.
- Aug 2024 – Sep 2026: Senior Engineer (AI & ML)
- Scoreline AI
- Owned the technical direction of the AI function for Fantasy Football Hub and Wickets.ai, Scoreline’s fantasy football and fantasy cricket products: the reference architecture for a multi-sport prediction platform, the predictions platform’s backend testing standard, and models across team strength, expected minutes and points prediction.
- Led the rebuild of Fantasy Football Hub’s prediction system, using proven, modern architecture (normalised data, event-driven services, serverless infrastructure) to make it faster, cheaper to run and safer to change.
- Built neural networks in PyTorch, from simple baselines to temporal attention over a player’s recent matches.
- Defined what a model has to satisfy to reach production: time-based evaluation splits and domain validation metrics, checked through backtesting.
- Proved the architecture on Wickets.ai before it was adopted into the main platform.
- Jan – Sep 2022, Sep 2023 – Aug 2024: Postdoctoral Research Fellow
- Predictive Analytics Lab, University of Sussex
- The second appointment held through the Basque Center for Applied Mathematics (BCAM), Bilbao.
- Developing other researchers and maintaining the lab’s shared engineering practice, alongside contributing to projects as a technical generalist.
- Lead author of the lab’s open-source experiment framework.
- Sep 2022 – Sep 2023: Career break
- Travel across Central and South America after submitting my PhD.
- Feb 2020 – Jan 2021: Consultancy Project Lead
- Predictive Analytics Lab, University of Sussex
- Led five researchers to deliver a documented Python library for a charity client, learning causal structure (Bayesian networks, via MCMC) from questionnaire data and estimating intervention effects.
- Sep 2017 – Sep 2018: Technology Graduate
- American Express
- Teams worked:
- Data Architecture: data access APIs and database migrations for a move to microservices
- Enterprise Cloud Platform: advising development teams adopting cloud systems
- Summer 2016: Technology Intern
- American Express
- Duties included: Database Migration
Skills
- Python, PyTorch, Lightning, Weights & Biases, scikit-learn, XGBoost, Pandas/NumPy
- Model evaluation, backtesting and monitoring; experiment tooling (Optuna, Hydra)
- Systems architecture, Postgres, Pulumi, Cloud Run, Pub/Sub
- Constrained optimisation (MILP)
Publications
Talks
Introduction to Fair Machine Learning
Summer School at University of Sussex, Data Intensive Science Centre, Brighton, UK
Does Fairness Come with a Cost?
Conference presentation at Fields Institute, Toronto, Canada
Introduction to Fair Machine Learning
Summer School at Ukranian Catholic University, Faculty of Applied Sciences, Lviv, Ukraine
Tools and tenets for ML and Python
Informal at University of Sussex - Predictive Analytics Lab,