SOP Sample for MS Data Science Applicants in GB

Two years ago, I identified a possibility in me to tell a story through the use of data. It was driven by my love for mathematics and a post-graduate diploma that taught me the basics of programming and the tools required to tell a story. Having completed a couple of projects, I felt I could push my capacity to learn even more so I continued exploring through mediums such as [PLATFORM_1], [PLATFORM_2], and [PLATFORM_3]. Today after having completed eight online courses of varying lengths and eight projects ranging from a simple regression model to the application of a real-time deep learning & computer vision model, I still feel there is much more to explore. This is where the program offered by your university comes in and has me applying with high hopes.

Having had some experience and learnings in management during my undergraduate studies and some experience in data analytics during my post-graduate diploma, I feel this course is an ideal stepping stone to building a successful career in this space.

A consistent performance in my undergrad studies opened new doors where I was fortunate enough to be selected as a head of the Student Council as well as the Admissions Committee. Coupled with an internship at [COMPANY_1], I feel inclined to be in sync with the management aspect of things. On the other hand, I was able to quickly adapt to the tech side of life when I enrolled myself at [INSTITUTION_1] where I pursued a diploma in Economics with a specialization in Data Analytics. I have gained some experience in various new tech fields and interned as a consultant with a real estate firm. My skills have expanded from Microsoft Excel & PowerPoint to Python, R, Matlab, Regression, and Classification.

After finishing my diploma in July of 2020, amid the coronavirus pandemic, I chose to continue exploring online studying at my end. I went with the path of being a protégé of influential professors such as [PROFESSOR_1], [PROFESSOR_2], and [PROFESSOR_3] on [PLATFORM_1] and [PLATFORM_2]. I remember my very first data science course being taught by the professors mentioned above and my very first machine learning project being a simple regression model that predicted the absolute and relative humidity in the air based on variables such as temperature, benzene concentration, nitrogen dioxide concentration, etc. I was fascinated by the realization that seconds of training could build a model that can be called upon at any time.

Several projects later I found myself working on complex ideas that involved the integration of deep neural networks with real-time computer vision to detect face masks through a webcam. The range of projects I've experimented with is considerably varied and engaging with other projects comprising sarcasm detection using natural language processing, optical character recognition (OCR) using PyTesseract, automation of Instagram through selenium to send direct messages to anyone, and anomaly detection in music using K-means clustering.

While the most oft-heard inspirations for entering the field are mentioned to be AI, Robots, or self-driving cars, what pulls me towards data science is its application in healthcare, medicine, and biotechnology. The fact that just by looking at certain pictures or numbers, a computer can determine if a cancer is benign or malignant, predict the probability of development of a disease, or detect patterns in symptoms to derive new insights about a new or existing disease is truly a revelation.

Perhaps, for this very reason, my personal favorite machine learning project is a simple classification model that predicts the outcome of a patient suffering from heart failure. Essentially, it is inspired by a research paper published by [JOURNAL_1] that claimed to predict the survival of patients with heart failure using two variables only. After an empathic trial and error session, I was able to increase the accuracy from 62-74% to 76-90% by including two more important variables. What I love most about the project is that it doesn't even make use of a million intricate neural network layers, it just uses the easiest algorithms built on foundations of basic math, which go on to contribute to the field in such a formidable way.

When it comes to this course, my goal would be to expand my knowledge to a point where I too can join a vibrant UK-based start-up and accord the field of healthcare in my own way. I chose London as my preferred destination because of two reasons. As an idolizer of Romanesque, Renaissance, and Gothic architecture, I find the city to be a divine amalgam of Victorian art styles and a utopia for anyone who appreciates art. On the other hand, I'm an ardent admirer of multiple AI-focused start-ups such as [COMPANY_2] (a start-up that uses AI/ML to improve or discover new ways to treat diseases), [COMPANY_3] (an AI-based platform that improves employee well-being, engagement, and productivity at scale) or [COMPANY_4] (an ambitious start-up that plans to use machine learning to revolutionize our convention of self-driving vehicles).

While my short-term goal after completion of the course would be to work as a junior data scientist at a FAANG company, once I am able to mentor junior data scientists, understand project scope, where to prioritize applications of data science and communicate technical concepts well, I would like to take up a Senior data scientist role at an early stage startup.

Pursuing a masters from your university will teach me new analytical skills and more importantly, how to blend the newly learnt tools in a pragmatic setting because while it is one thing to complete a project in over a weekend on your local editor, it is another to come together as a team and build large-scale models over time that actually grow a business. I'm extremely excited to gain experience in the latter and at the same time, I'm entirely aware of the commitment and efforts required to suit this endeavor. I feel confident in my abilities and I plan to strive forth with a dedicated tenacity to embrace the challenges and learnings this course would introduce me to.

I thank you for your time and consideration and I wish us the best of luck.