My journey of mathematics and CS - motivational letter for data science

Here's the requirement:

The letter of motivation

is intended to explain the reasons you have chosen the specific programme at KTH, and what you hope to gain from it. Include a short autobiographical statement covering the development of your academic and professional pursuits, extra-curricular activities, the relevance of your academic, professional, and other related experience to your proposed study at KTH. A well-written letter of motivation will explain why you want to further your studies in your chosen program, and how your interests and skills will contribute to your success in the programme, and to your future career. Your letter of motivation should not exceed 500 words (no more than one page) and must be written in English.

Here's the motivational letter that I have drafted, I'd appreciate it if anyone can give me some advice. great thanks

I am incredibly fortunate to embark on the exciting journey of mathematics and CS with various interdisciplinary projects in my college life, which made me realize the power of data in interpreting how the world works and expanding the boundary of knowledge. I genuinely believe that is where my passion belongs. Therefore, I am determined to pursue the master's degree in Computer Science (Data Science track) at KTH.

I benefited a lot from my undergrad training which laid a solid foundation for me. I have achieved a major GPA of 3.71 in compulsory courses and strong performance in such computational mathematics courses as Numerical Analysis and Optimization with a score of 91 and 93 out of 100 for both. In these courses, I felt the flow state when I implemented algorithms from the textbook, which I believe is the main drive for me to keep exploring in related fields. Furthermore, I have poured this passion into projects of interpreting unstructured data and genetical datasets. All these learnings and projects naturally grew my interest in data science and improved my skills in algorithms and data-processing techniques.

To explore data in another dimension, I work as a CV Algorithm Engineer intern at AsiaInfo starting from June 2020. I have successfully built production-level facial recognition models on mobile platforms, both arm-based and x86-based Linux using java, c++, and python. I also worked on the improvement and maintenance of the backend system for components of facial recognition systems such as Redis, flask, celery. Despite a lot of challenges involving incompatibility or compilation errors, I was able to overcome them by my self-learning abilities, as well as effectively seeking advice from others.

During my internship, I have exchanged ideas with our team on anti-spoofing facial recognition, which made me realize that deep learning faces pressing issues such as interpretability and domain adaptation. At the same time, I happened to be reading The Book of Why written by Judea Pearl, an expert in causal statistics. Pearl vividly describes how causal science can be a game-changing part of future algorithms and that fascinates me. I believe that courses on statistics (Statistical Methods in Applied Computer Science or Probabilistic Graphical Models) in this program can advance my knowledge in causal science, and courses on deep learning can help me gain new perspectives.

Eventually, I want to pursue a Ph.D. degree in Decision and Control Systems, which is a research branch at your university. And I have already dived into this area with my dissertation project on Bayesian multi-agent cooperation. I look forward to attending DD2438 (Artificial Intelligence and Multi-Agent Systems) for fresher experience and apply causal-deep learning to this field in the future. I believe this program of MSc in CS at KTH is a perfect match for my goal. The strong academic atmosphere, a wide variety of lectures and seminars, and well-organized course structure could extend my expertise to the next level.

Your writing is coherent and perfect.
However, I think you should concretise your achievements by adding statistics results or certifications.

Hope that could help you.

The first paragraph is not useful. You should not waste word count on useless backstories that do not advance your story or inform the reviewer. You should remove that paragraph and instead, discuss how your interest in Data Science has developed since you graduated. Open the essay with your current career path and how it relates to your interest in Data Science. Having explained that, use a new paragraph to discuss how you performed in classes related to Data Science during your undergraduate time. This should help explain the skills that you developed as a student and how you apply it in your current job. The internship discussion is relevant, but covers too much of your presentation. There should be more of a focus on your current profession, any training or seminar you attended that could prove relevant to the masters course you are taking, and an explanation of your university choice. The PhD reference is too far reaching and currently irrelevant to the discussion.