Prompt: why you want to do this master (interests, career path), why you qualify for it (strengths).
My doubt: Is this line of reasoning okay? will a lack of pure quantitative experience disqualify me directly?
Dear Members of the Admissions Committee,
My interest in financial markets began when I realized how closely they reflect human behaviour. Every price movement captures a collection of beliefs, expectations, and reactions. What fascinated me most was how much data exists within that system, and how patterns in it can help explain or even predict how markets might move. That curiosity about finding structure within uncertainty is what drew me toward quantitative finance.
I studied Mechanical Engineering and graduated with First Class Honours. While my coursework was fairly standard, I found myself drawn to the mathematical side of it, especially subjects like Probability Theory, Numerical Methods, and Linear Algebra. I have always done well in math, but looking back, I feel I did not study it as deeply as I would have liked. Over time that feeling has turned into a clear goal: to build a stronger mathematical foundation and apply it to financial problems.
I began my career at (Big Bank), working in liquidity reporting. My role involved analysing behavioural cashflow models and stress-testing frameworks to measure liquidity risk. This experience introduced me to the mechanics of financial modelling and the idea of managing uncertainty with structure and data. I later joined (Investment Bank), where I currently work in the model review function within the risk division. I review methodologies used across risk teams, ensuring they are sound, compliant, and conceptually consistent. It has been a great learning experience, and it has shown me both the importance and the limitations of qualitative oversight. I often find myself wanting to design or improve the models I review, but I know I need stronger quantitative skills to do that effectively.
Outside of work, I have been developing those skills on my own. I built simple Python scripts to test how well classical candlestick patterns predict stock movements, which gave me a practical way to connect statistics with financial data. It was a small project, but it reminded me how much I enjoy working with numbers and analytical thinking.
I want to study at ETH Zurich because it offers exactly the kind of academic depth and structure I need. The program's focus on financial mathematics, risk management, and data-driven methods matches both my background and my goals. I learn best by breaking things down to first principles, and I believe the program's interdisciplinary approach across finance, mathematics, and computer science will challenge me in the right ways.
Having worked in risk management from an operational and governance point of view, I now want to move into its quantitative core. My goal is to work on model development and validation, building tools that help measure financial risk more accurately. I am confident that ETH Zurich provides the best environment to make that transition.
Thank you for considering my application.
My doubt: Is this line of reasoning okay? will a lack of pure quantitative experience disqualify me directly?
Dear Members of the Admissions Committee,
My interest in financial markets began when I realized how closely they reflect human behaviour. Every price movement captures a collection of beliefs, expectations, and reactions. What fascinated me most was how much data exists within that system, and how patterns in it can help explain or even predict how markets might move. That curiosity about finding structure within uncertainty is what drew me toward quantitative finance.
I studied Mechanical Engineering and graduated with First Class Honours. While my coursework was fairly standard, I found myself drawn to the mathematical side of it, especially subjects like Probability Theory, Numerical Methods, and Linear Algebra. I have always done well in math, but looking back, I feel I did not study it as deeply as I would have liked. Over time that feeling has turned into a clear goal: to build a stronger mathematical foundation and apply it to financial problems.
I began my career at (Big Bank), working in liquidity reporting. My role involved analysing behavioural cashflow models and stress-testing frameworks to measure liquidity risk. This experience introduced me to the mechanics of financial modelling and the idea of managing uncertainty with structure and data. I later joined (Investment Bank), where I currently work in the model review function within the risk division. I review methodologies used across risk teams, ensuring they are sound, compliant, and conceptually consistent. It has been a great learning experience, and it has shown me both the importance and the limitations of qualitative oversight. I often find myself wanting to design or improve the models I review, but I know I need stronger quantitative skills to do that effectively.
Outside of work, I have been developing those skills on my own. I built simple Python scripts to test how well classical candlestick patterns predict stock movements, which gave me a practical way to connect statistics with financial data. It was a small project, but it reminded me how much I enjoy working with numbers and analytical thinking.
I want to study at ETH Zurich because it offers exactly the kind of academic depth and structure I need. The program's focus on financial mathematics, risk management, and data-driven methods matches both my background and my goals. I learn best by breaking things down to first principles, and I believe the program's interdisciplinary approach across finance, mathematics, and computer science will challenge me in the right ways.
Having worked in risk management from an operational and governance point of view, I now want to move into its quantitative core. My goal is to work on model development and validation, building tools that help measure financial risk more accurately. I am confident that ETH Zurich provides the best environment to make that transition.
Thank you for considering my application.
