jayath2016
Jan 11, 2018
Graduate / Statement of purpose for Masters in Data Sciences at Columbia University [2]
It was in the thick of the digital or information age that I entered high school. What's more, I was a computer gaming freak, with an analytical and mathematical bent. I recall being wonderstruck by increasing levels of difficulty in higher levels of the game based on moves made by the player in lower levels. This was my first brush with the impact of data sciences in using real-time data towards an innovative and exciting end user benefit. This interest in the role of data and computers in the layperson's life persisted and by the time I reached the senior secondary level, it was quite natural for me to set my heart on an IT-related career. Thus, after completing Class XII, I cleared the all-India engineering entrance exam and got myself admitted to the B.Tech program in Computer Science and Engineering at GITAM Institute of Technology.
During my undergraduate studies, I enjoyed all the courses related to programming, particularly C, C++, Java, HTML, PHP and so on. In spite of my above-average performance, I have had an unexpected academic setback in my 1st semester when I failed in one of the courses. This was partially due to certain health issues that I faced. Nevertheless, I worked hard this time and completed the course with a good grade in the 2nd semester itself, for I do not believe in throwing pity parties for my self. Thereafter, I kept improving my performance with each successive semester, finally scoring a decent cumulative GPA of 7.49 at the end of the program.
After completing my undergraduate studies in 2014, I joined a start-up called Ebutor, whose core business was e-commerce (B2B). In the capacity of a Software Programmer, my main responsibilities were automation testing and manual testing, using Java program. Unfortunately, soon after the third year of its inception, Ebutor found itself becoming unviable. Following the subsequent layoff and restructuring, I had to separate from the company. However, I did not give up. I knew that if one had the determination, one could turn every crisis into an opportunity.
Being out of work and thus having enough free time at my disposal, it was the right opportunity for me to introspect. I realized that automation testing was set to become outdated over the next five years or so. Therefore, in any case, it was imperative for me to reskill or upskill myself for a promising future. I was fascinated by the unique success story of LinkedIn, which owed its current stature to Data Science. LinkedIn had, in fact, struggled initially as the company's site was not developing the way its founders had envisaged. Then, after a few rounds of brain-storming, the founders decided to segregate the data with the help of Data Science tools and methodologies including heuristics.
Now LinkedIn has a million profiles on its site. Had its founders not thought of Data Science, LinkedIn would not have reached where it is today. Not surprising that Data Science was hailed by an expert as "one of the sexiest jobs of the 21st century". After doing some serious research, I gathered that the Data Science industry the world over was running short of trained and competent professionals. There was a tremendous scope for Data Scientists in Service-based and product-based companies as also Software as a Service (SaaS)-based companies.
While making a thorough self-assessment of my work experience, it occurred to me that the e-commerce projects handled by my former company often involved the application of data science methodologies. For instance, we used to recordour customers' buying history, monitor the trends in their likes and dislikes, evolve a pattern from their product ratings and make recommendations to prospective customers based on such patterns. My work at Ebutor also demanded statistical and mathematical knowledge, programming finesse, problem-solving ability, the ingenuity for data capturing, and the special knack of looking at data differently to find patterns. I realized that this was precisely what Data Science was all about. Further, my role at Ebutor was also¬ linked-indirectly, if not directly-to data cleansing, preparation, and analysis, and finally extracting insights from data, which are the roles performed by a Data Scientist.
Soon, I arrived at the decision that the best option for me would be to pursue graduate studies in the field that was basically in alignment with my undergraduate training and three years of work experience. Thus, I zeroed in on MS in Computer Science, with specialization in Data Science. I would like to do my graduate studies in one of the respected universities in the US, preferably in the State of California. After completing my MS, I would like to work as a Data Scientist in one of the leading tech companies. Subsequently, after acquiring sufficient professional competence and confidence over the next five to ten years, I wish to launch my own dream company.
On the strength of my academic performance at the undergraduate level, my substantially relevant work experience as a Software Programmer spanning over three years, and the considerable spadework I have been undertaking in preparation for my graduate studies, I wish to seek admission to the MS program in Computer Science (with specialization in Data Science) offered by your esteemed university. I expect that the MS program will essentially help me acquire a vast range of skills that Data Scientists need to possess. I am determined to gain in-depth knowledge of Statistics and a rigorous understanding of Machine Learning Algorithms for building predictive models, along with computer skills such as Querying Languages like SQL, Hive & Pig and Scripting Languages like Python & Matlab, Statistical Languages like R, SAS & SPSS. I hope the program will inculcate in me good interactive skills, leadership, and entrepreneurial competencies, as well as an appreciation of different cultures, too. I truly look forward to an exciting and fulfilling time at columbia university.
one of the sexiest jobs?
It was in the thick of the digital or information age that I entered high school. What's more, I was a computer gaming freak, with an analytical and mathematical bent. I recall being wonderstruck by increasing levels of difficulty in higher levels of the game based on moves made by the player in lower levels. This was my first brush with the impact of data sciences in using real-time data towards an innovative and exciting end user benefit. This interest in the role of data and computers in the layperson's life persisted and by the time I reached the senior secondary level, it was quite natural for me to set my heart on an IT-related career. Thus, after completing Class XII, I cleared the all-India engineering entrance exam and got myself admitted to the B.Tech program in Computer Science and Engineering at GITAM Institute of Technology.
During my undergraduate studies, I enjoyed all the courses related to programming, particularly C, C++, Java, HTML, PHP and so on. In spite of my above-average performance, I have had an unexpected academic setback in my 1st semester when I failed in one of the courses. This was partially due to certain health issues that I faced. Nevertheless, I worked hard this time and completed the course with a good grade in the 2nd semester itself, for I do not believe in throwing pity parties for my self. Thereafter, I kept improving my performance with each successive semester, finally scoring a decent cumulative GPA of 7.49 at the end of the program.
After completing my undergraduate studies in 2014, I joined a start-up called Ebutor, whose core business was e-commerce (B2B). In the capacity of a Software Programmer, my main responsibilities were automation testing and manual testing, using Java program. Unfortunately, soon after the third year of its inception, Ebutor found itself becoming unviable. Following the subsequent layoff and restructuring, I had to separate from the company. However, I did not give up. I knew that if one had the determination, one could turn every crisis into an opportunity.
Being out of work and thus having enough free time at my disposal, it was the right opportunity for me to introspect. I realized that automation testing was set to become outdated over the next five years or so. Therefore, in any case, it was imperative for me to reskill or upskill myself for a promising future. I was fascinated by the unique success story of LinkedIn, which owed its current stature to Data Science. LinkedIn had, in fact, struggled initially as the company's site was not developing the way its founders had envisaged. Then, after a few rounds of brain-storming, the founders decided to segregate the data with the help of Data Science tools and methodologies including heuristics.
Now LinkedIn has a million profiles on its site. Had its founders not thought of Data Science, LinkedIn would not have reached where it is today. Not surprising that Data Science was hailed by an expert as "one of the sexiest jobs of the 21st century". After doing some serious research, I gathered that the Data Science industry the world over was running short of trained and competent professionals. There was a tremendous scope for Data Scientists in Service-based and product-based companies as also Software as a Service (SaaS)-based companies.
While making a thorough self-assessment of my work experience, it occurred to me that the e-commerce projects handled by my former company often involved the application of data science methodologies. For instance, we used to recordour customers' buying history, monitor the trends in their likes and dislikes, evolve a pattern from their product ratings and make recommendations to prospective customers based on such patterns. My work at Ebutor also demanded statistical and mathematical knowledge, programming finesse, problem-solving ability, the ingenuity for data capturing, and the special knack of looking at data differently to find patterns. I realized that this was precisely what Data Science was all about. Further, my role at Ebutor was also¬ linked-indirectly, if not directly-to data cleansing, preparation, and analysis, and finally extracting insights from data, which are the roles performed by a Data Scientist.
Soon, I arrived at the decision that the best option for me would be to pursue graduate studies in the field that was basically in alignment with my undergraduate training and three years of work experience. Thus, I zeroed in on MS in Computer Science, with specialization in Data Science. I would like to do my graduate studies in one of the respected universities in the US, preferably in the State of California. After completing my MS, I would like to work as a Data Scientist in one of the leading tech companies. Subsequently, after acquiring sufficient professional competence and confidence over the next five to ten years, I wish to launch my own dream company.
On the strength of my academic performance at the undergraduate level, my substantially relevant work experience as a Software Programmer spanning over three years, and the considerable spadework I have been undertaking in preparation for my graduate studies, I wish to seek admission to the MS program in Computer Science (with specialization in Data Science) offered by your esteemed university. I expect that the MS program will essentially help me acquire a vast range of skills that Data Scientists need to possess. I am determined to gain in-depth knowledge of Statistics and a rigorous understanding of Machine Learning Algorithms for building predictive models, along with computer skills such as Querying Languages like SQL, Hive & Pig and Scripting Languages like Python & Matlab, Statistical Languages like R, SAS & SPSS. I hope the program will inculcate in me good interactive skills, leadership, and entrepreneurial competencies, as well as an appreciation of different cultures, too. I truly look forward to an exciting and fulfilling time at columbia university.
