About Me

My background includes notable research contributions in fluid dynamics and mathematical physics, with several publications in prestigious academic journals and special issues. Passionate about the synergy of mathematics, programming, and finance, I employ analytical methodologies and concepts in statistics and machine learning to develop/validate models and address challenges related to credit and market risk.

Professional Experience

Credit Risk Consultant, TNP, September 2023-Present:

Project experience:

• Validating credit risk models, ranging across IFRS 9, market risk, pricing and scorecards
• Collecting and presenting market research, assessing competition and product offerings in the banking industry
• Validating macroeconomic SARIMAX and regression models by assessing stability and other statistical properties
• Exploring account data to assess and re-calibrate signature curve methodology to derive risk grades
• Producing modular Python code for data analysis, making use of OOP principles, data structures and unit tests
• Writing documentation that details the mathematics and methodology employed during the project life cycle
• Balance sheet management, forecasting and ICAAP development

Postdoctoral Researcher, Imperial College London, July-August 2023:

Contributions:

• Published in the special issue ‘Nonlinear Phenomena in Fluid Dynamics’ in the journal ‘Physica D’
• Published in the special issue ‘Coherent Vortices’ in the journal of ‘Physics of Fluids’

Reasearch Summary:

• Characterised the instability of quasi-geostrophic eastward dipole steady states by a critical Davies mode using high-resolution numerical simulations
• Verified the linear instability of eastward dipoles by obtaining solutions to the complete eigenproblem
• Investigated the influence of tilting on the dipole instability, including scenarios of steady state adjustment
• Formulated the nonlinear destruction mechanism and associated energetics of eastward dipoles
• Briefly explored the dynamics of dipole-rider vortices and how they compared with the unstable dipole counterpart

Actuary Intern, First Actuarial, June-July 2022:

Pensions:

• Was introduced to defined contribution and defined benefit schemes
• Gained proficiency in Excel: cleaning, manipulating, and visualising data
• Performed transfer value calculations, incorporating: late retirement factors, annuity adjustment and GMP equalization
• Engaged with: client verification, factor review, actuarial reporting and sensitivity analysis

Investments:

• Obtained knowledge of bonds, commodities, derivatives, equities, swaps and how they behave in different economic scenarios
• Presented a talk on “Investment Insight for Pension Schemes” to founders and partners of the firm

Education

PhD in Mathematical Physics, Imperial College London, 2019-2023:

Contributions:

• Published in prestigious academic journals, including the ‘Journal of Fluid Mechanics’ and ‘Physics of Fluids’
• Was a graduate teaching assistant across all year groups, including the final year modules in ‘Numerical solution of ordinary differential equations’ and ‘classical dynamics’

Development:

• Obtained strong programming skills in MATLAB and Fortran

Certificate in Quantitative Finance (CQF), Fitch Learning, 2022-2023:

Achievements:

• Completed with Distinction (final exam mark of 81%) - overall average of 79%

Quantitative Finance:

• Mathematics: stochastic calculus, martingales, solution techniques to PDEs and numerical linear algebra
• Financial engineering: portfolio optimisation, risk management, option pricing models, Monte Carlo simulation, volatility arbitrage and fixed income derivatives

Machine Learning:

• Supervised learning: K-nearest neighbours, support vector machines, naive Bayes classifiers, decision trees, regression methods
• Unsupervised learning: K-means clustering, self-organising maps and neural networks
• Advanced topics: reinforcement learning and quantum computing

MSc in Applied Mathematics, Imperial College London, 2018-2019:

Achievements:

• Completed with Distinction - dissertation awarded 86%

Masters Year:

• My studies included: asymptotic analysis, PDE theory, inviscid fluid dynamics, geophysical fluid dynamics, vortex dynamics, hydrodynamic instability, numerical methods for ODEs/PDEs and function spaces

BSc in Mathematics, The University of Nottingham, 2015-2018:

Achievements:

• Completed with First Class Honours - final year dissertation awarded 79%

Studies:

• First year: probability, statistics, multivariable calculus, linear algebra, real analysis, elementary group/number theory and applied mathematics
• Second year: real/complex analysis, Markov chains, classical mechanics, elementary quantum mechanics, Fourier analysis, vector calculus, phase plane analysis and PDEs
• Third year: advanced quantum mechanics, general relativity, mathematical biology, viscous fluid dynamics, perturbation methods and bifurcation theory