Curriculum Vitae

Industry Experience

Machine Learning Researcher, Civil Service (Mar 2024 - Oct 2025)

• Suspended my PhD studies for a six-month placement in the civil service.
• Researched and implemented machine learning methods using JAX.
• Collaborated within an Agile development team, running GPU workloads on AWS instances accessed via SSH.

Data Quality Analyst, Beauhurst (Temp, Jun 2019 - present)

• Work around 20 hours per week alongside full-time undergraduate and PhD studies.
• Responsible for maintaining the quality of the company’s database of fast-growing UK businesses. Tasks include categorising companies based on online and financial activity, gathering and publishing relevant news, and ensuring key employee information remains up to date.
• Review and approve edits made by other team members before pushing verified updates live to subscribers.
• Conducted ad-hoc machine learning project developing an NLP model in Python (using NLTK) to detect when a company has rebranded or pivoted. This involved computing similarity scores between old and new company blurbs and tuning a threshold hyperparameter to automatically flag cases requiring further review.

Education

PhD, Computational Statistics and Data Science, Compass CDT, University of Bristol, School of Mathematics. (2021 - 2026)

• 1st year MRes in statistical methods and computing (85% average).
• Co-organiser for the 1st and 2nd annual Compass conference.

MMath, Mathematics with Statistics at the University of Nottingham, School of Mathematical sciences (2017 - 2021)

• First class honours (86% average).
• Nottingham School of Mathematics Achievement Prize (2018, 2019, 2021).
• Nottingham School of Mathematics Poster Prize (2020).
• Peer Assisted Study Support (PASS) Leader (2018 - 2021), organising study support sessions for first year students.

The Brooksbank School (2013-2017)

• A Level Mathematics (A*), Physics (A*), Chemistry (A*), Extended Project (A*), AS Level Further Mathematics (A), Biology (A).
• 10 GCSEs, 9A*s, 1 A.

Technical Skills

• Tools: Proficient in Python and R, with extensive experience using Linux, Bash, and Git for development. Experience with unit testing via pytest for robust code development. Familiar with SLURM for high-performance computing and AWS for cloud-based GPU workloads.
• Packages: Experienced with the Python and R scientific ecosystems, including NumPy, Pandas, Matplotlib, SciPy, Scikit-learn, PyTorch, JAX, NumPyro, Jupyter, R Markdown, Tidyverse, and ggplot2.

For publications, personal projects and additional research projects see the top of the site.