Data Science Masters - Columbia University Personal Statement

Hi,

Please review my PS for MS in Data Science at Columbia University.

Comments/Questions :
I haven't made it as an autobiography as this is the only essay required in the application (made it more of a SOP style).

I am planning to start it as a Part time with job and later on moving to a Full time couse (after 4 foundational courses I would say), do I need to mention this fact or keep it out the Statement?

Another thing is I haven't found any faculty member to mention here. Shall I do more research and add a line for them at the end?

Thanks

Personal Statement

Describe how your professional and academic background has prepared you to pursue an advanced degree in the field of engineering or applied science at Columbia University. If there are any special circumstances that need to be brought to the attention of the Admission Committee, please include that information.

Over the past six years, my work opportunities as a Software Engineer have largely involved Analytics in various domains like finance, healthcare, and online gaming. To understand the hidden patterns and parameters of the ever-growing data governing the complex market and business decisions, constant efforts are needed to develop advanced analytics on pace with the rapid growth of data. My robust, practical experience working as a Software Engineer has continuously affirmed my desire to shift my focus to data science. However, my experiences have also exposed my knowledge gaps and motivated me to pursue an advanced degree program to address my knowledge gaps and position myself to excel in the data science field. After comparing programs that I felt aligned with my professional aspirations, I believe that the Master of Science in Data Science (MSDS) degree offered by the Columbia University will provide me an opportunity to further move from the operational understanding of a Business Intelligence Engineer to the deeper modeling perspective of a Data Scientist.

As an undergraduate, although my focus was mainly Electronics and Communication Engineering, I amassed theoretical knowledge in essential subjects a software engineer needs to have such as computer organization and architecture, computer networks, data structures, computer engineering, and internet applications. I also took relevant courses such as mathematics-I, II, and III which emphasized core competencies in linear algebra, calculus, statistical methods, and operational research. I also independently learned C++; object-oriented programming concepts; algorithms and analysis; and secured a software engineer job during campus recruitment.

Currently, I work as a Business Intelligence Engineer at an asset management firm. There, I work on projects that revolve around programming, visual analytics, and data management. I am responsible for end-to-end development of analytics dashboards used by the Investment and Risk teams to make business decisions. Being a part of the analytics team has provided me with invaluable experience in supporting business users to help drive solution improvements, financial forecasting, and process development. As projects evolve and grow with complex market needs, I am eager to advance my knowledge in machine learning.

During the last two years, I gained substantial experience in Data Science by attending various NYC meetups and Machine Learning nights. In further relevance to my work, I have undertaken the Verified course and certification for The Analytics Edge by MIT from edX where I gained wider exposure to the use of ML techniques in different domains. I also attended a five-day immersive Data Science boot camp that covered the basics of ML algorithms, big data, a mix of theory, hands-on labs, and a Kaggle competition. I also fortified my knowledge of Computer Science by taking online courses and specializations focused on Data Analytics, Python, R, Tableau, and Machine Learning.

I am excited about the opportunities presented by the Data Science Institute at Columbia University that will help me acquire the requisite skills to establish myself in the data science field and eventually emerge as an industry leader. Courses such as Machine Learning, Deep Learning, and Natural Language Processing will expand my academic horizons and help me in using the available data precisely. After graduating from Columbia University, I would like to work as a Data Scientist, preferably in the finance or healthcare industry and have proficiency in designing experiments, interpreting the data, and inferring conclusions. Also, I would like to keep abreast of biases of the models and manage Data Science teams in the future.

I look forward to gaining a competitive edge by deepening my understanding of various statistical and analytical techniques and upgrading my technical skills through the well-structured curriculum at Columbia. Columbia University is one of the top-ranking schools for Computer Science and Statistics and it will be my privilege to study at such a prestigious institute. Learning through interaction with the renounced faculty, industry leaders, and data science peers will add to the exciting experience of graduating from Columbia University. I am positive that the course structure, curriculum and the real-world approach during the MSDS program offered at Columbia University will play a decisive role in my life, both as a student and as a professional.

Gautam, this is a very strong essay. I would call it highly competitive and should receive proper consideration from the reviewer. It can only be strengthened by the addition of the information that you plan to pursue this course part time at first before going headlong into the full course requirements later on. That is part of the special circumstance discussion that the prompt is talking about. Be sure to describe how you plan to progress from part-time student to full-time student to show that you are not taking the masters course lightly and that you have every attention of applying yourself properly to the course and its requirements.

Since the information about the professor is not indicated in the prompt, you don't have to worry about it. It is not required information so the reviewer won't even notice it is missing. It doesn't appear to be something that the reviewer will consider important otherwise the instructions for writing the essay would have specifically required it. You can skip that presentation without worries.

The last paragraph is too generic sounding for it to help you close the essay on a strong note. Try to go for more specifics regarding what you hope to learn at the university and how. Use lab exposure, internships, or notable courses which you feel will help make a better data scientist out of you instead. That will show a real familiarity with the university and its course requirements for the completion of this masters degree.