
Motivated and detail-oriented engineering student with strong analytical, numerical, and programming abilities, developed through both academic study and hands-on technical work. Skilled in applying mathematical methods, data analysis, and structured problem-solving to real-world challenges, with growing interest in quantitative finance and financial markets. Experienced in fast-paced environments where accuracy, safety, and clear communication are essential. Currently seeking an opportunity to further build quantitative skills, develop financial modelling experience, and contribute effectively within collaborative, high-performance teams.
Programming & Analytical Tools: Proficient in Python and MATLAB for numerical modelling, data handling, and visualising trends to support analytical decision-making
Data Analysis & Reporting: Skilled in Excel and PowerPoint for organising datasets, applying formulas, interpreting results, and presenting clear quantitative insights
Mathematical & Statistical Reasoning: Strong understanding of probability, statistics, linear algebra, and calculus, applying these concepts to solve data-driven and computational problems
Financial Market Awareness: Practical familiarity with stock and crypto trading platforms, analysing market movements, volatility patterns, and basic investment indicators
Simulation & Modelling Software: Experience using Simulink and Multisim to simulate system behaviour, evaluate performance trends, and interpret numerical results from model outputs
Algorithmic & Computational Thinking: Exposure to C and MATLAB scripting for algorithm development, studying relationships between variables, and optimising analytical processes
Communication: Able to translate technical and numerical findings into clear explanations for both technical and non-technical audiences
Teamwork: Effective collaboration within diverse academic project groups, contributing quantitative perspectives to achieve shared goals and complete analytical tasks
Problem Solving: Strong capability in approaching complex challenges logically, applying structured reasoning to identify causes and propose data-informed solutions