Hello, I would be applying to NYU, Stanford, Harvard, USC, and GeorgiaTech for an MS in Data Science. Could you please help me look for grammatical errors and provide me with suggestions for this Statement of Purpose?
During the summer of 2017, when I was an intern at Sonata Software Limited, I was assigned the task of building a portal for the company's sales and marketing team which would retrieve user information from various cloud service providers, analyze the data based on a few parameters, and then provide the user with recommendations based on their cloud usage. It was at this time that I came across several techniques which could be used to perform the analysis and provide the user with appropriate recommendations.
It just so happened, that at that time, I ended up reading a lot of articles and papers related to this new, emerging field of 'Data Science' which was in vogue at that time. Subsequently, I made the decision of exploring this field further and ended up taking elective courses and doing projects which involved more of data analysis and statistics.
Over the course of the next two semesters, my electives included courses such as Data Mining, Artificial Intelligence, Information Retrieval, Econometrics, Financial Mathematics, which improved my statistical knowledge, and at the same time, gave me the opportunity to apply the concepts which I learned to the interesting assignments which were assigned to us as part of the course structure.
At the same time, I began working on a few personal projects too. The first one was a comprehensive analysis of the economics of cloud computing and its comparative advantage in comparison to grid computing. As part of the project, I was supposed to collect cloud and grid usage data across various sectors and industries, and that gave me a deeper understanding of the entire data collection and selection process.
My second project explored the possibility of using a chatbot and predictive algorithms to make disease predictions based on the conversations which a user might have with the chatbot. I ended up pitching this idea at a few local hackathons, and to my surprise, it attracted a lot of attention and investors who believed in the project and wanted it to be a consumer application.
I also worked on a project which involved the extraction of tweets from Twitter. The sentiments of these extracted tweets were then found out using different techniques such as neural networks, support vector machines, and k-NN. Eventually, the daily aggregates of such sentiments were mapped against the real-world stock prices to see if there was any correlation between the two. To take the project a step further, I ended up using cellular automata and agent-based modelling techniques to forecast sentiments and then check for a correlation with stock market prices.
During the course of these semesters, I participated in various competitions which involved the analysis of big data. One such competition was hosted by the 3M Group who wanted students to design a campaign to promote their new line of products. The team which I was a part of got selected and made it into the finals of the competition where we presented a completely data-driven solution to marketing and identifying potential target customers. I also ended up participating in WorldQuant's International Quant Challenge, where I was a part of the team which placed first in the Middle East and North Africa region.
The following summer, I had the opportunity to intern at LinkedIn's Bengaluru Office as a Data Scientist working with the Analytics team. I was assigned the task of analysing the company's Hiring Marketplace Dynamics for the quarter, and automating this task using tools - both, internal and external, such as Alation, Presto, Pig, Hive, Teradata, FastML, Spark, EasyData, Raptor, and Azkaban. In a short period of six weeks, I was exposed to a huge amount of both, structured and unstructured data
Performing an analysis of the LinkedIn global user data against multiple parameters and filters was no easy task, and as a novice, I fumbled, initially. But, over time, with the help of my mentor and my manager, I ended up completing the project on time and by the end of the internship, I was able to understand the entire database structure of the company and the way that most of the data was being tracked and used to improve the platform. Since my project had multiple stakeholders, it also helped me develop my collaborative and communication skills as I had to work as a part of a team spread across different parts of the globe.
This internship also gave me the chance to work and interact with some of the best Data Scientists. The learning curve was steep and sometimes, the going did get tough, but by the end of it all, I realized that Data Science was the field which I was passionate about.
Currently, I am working as an Intern at Crowe, Dubai, and as a part of this internship, I have had the opportunity to work on creating databases for the company's various portals, writing triggers, and functions for automating certain tasks such as the scheduling of meetings and storage of documents.
All these experiences so far, have given me an exposure on working with all aspects of the data science spectrum such as data collection, storage, retrieval, analytics, and prediction. Each and every single one of these aspects have improved my skillset and provided me with a deeper understanding of what Data Science is actually about.
In a world surrounded by petabytes of data spanning diverse fields, the fact that I could extract useful information, analyze it and provide people with recommendations or suggestions which could improve their lives is what makes me want to pursue a career in this field. And, with the help of XXXXX University's Data Science program, I could certainly polish and sharpen my skills while being surrounded by some of the world's best professors, researchers and students, and eventually become the best at what I do.
The XXXXX University's program is one which is a perfect fit for me as it would provide me with the flexibility of choosing the courses which I want to learn more about, and at the same time, use the University's strong alumni network and location to meet and interact with professionals with whom I could, potentially, collaborate, research, and work with on projects which could make the world a better place.
MS in Data Science
During the summer of 2017, when I was an intern at Sonata Software Limited, I was assigned the task of building a portal for the company's sales and marketing team which would retrieve user information from various cloud service providers, analyze the data based on a few parameters, and then provide the user with recommendations based on their cloud usage. It was at this time that I came across several techniques which could be used to perform the analysis and provide the user with appropriate recommendations.
It just so happened, that at that time, I ended up reading a lot of articles and papers related to this new, emerging field of 'Data Science' which was in vogue at that time. Subsequently, I made the decision of exploring this field further and ended up taking elective courses and doing projects which involved more of data analysis and statistics.
Over the course of the next two semesters, my electives included courses such as Data Mining, Artificial Intelligence, Information Retrieval, Econometrics, Financial Mathematics, which improved my statistical knowledge, and at the same time, gave me the opportunity to apply the concepts which I learned to the interesting assignments which were assigned to us as part of the course structure.
At the same time, I began working on a few personal projects too. The first one was a comprehensive analysis of the economics of cloud computing and its comparative advantage in comparison to grid computing. As part of the project, I was supposed to collect cloud and grid usage data across various sectors and industries, and that gave me a deeper understanding of the entire data collection and selection process.
My second project explored the possibility of using a chatbot and predictive algorithms to make disease predictions based on the conversations which a user might have with the chatbot. I ended up pitching this idea at a few local hackathons, and to my surprise, it attracted a lot of attention and investors who believed in the project and wanted it to be a consumer application.
I also worked on a project which involved the extraction of tweets from Twitter. The sentiments of these extracted tweets were then found out using different techniques such as neural networks, support vector machines, and k-NN. Eventually, the daily aggregates of such sentiments were mapped against the real-world stock prices to see if there was any correlation between the two. To take the project a step further, I ended up using cellular automata and agent-based modelling techniques to forecast sentiments and then check for a correlation with stock market prices.
During the course of these semesters, I participated in various competitions which involved the analysis of big data. One such competition was hosted by the 3M Group who wanted students to design a campaign to promote their new line of products. The team which I was a part of got selected and made it into the finals of the competition where we presented a completely data-driven solution to marketing and identifying potential target customers. I also ended up participating in WorldQuant's International Quant Challenge, where I was a part of the team which placed first in the Middle East and North Africa region.
The following summer, I had the opportunity to intern at LinkedIn's Bengaluru Office as a Data Scientist working with the Analytics team. I was assigned the task of analysing the company's Hiring Marketplace Dynamics for the quarter, and automating this task using tools - both, internal and external, such as Alation, Presto, Pig, Hive, Teradata, FastML, Spark, EasyData, Raptor, and Azkaban. In a short period of six weeks, I was exposed to a huge amount of both, structured and unstructured data
Performing an analysis of the LinkedIn global user data against multiple parameters and filters was no easy task, and as a novice, I fumbled, initially. But, over time, with the help of my mentor and my manager, I ended up completing the project on time and by the end of the internship, I was able to understand the entire database structure of the company and the way that most of the data was being tracked and used to improve the platform. Since my project had multiple stakeholders, it also helped me develop my collaborative and communication skills as I had to work as a part of a team spread across different parts of the globe.
This internship also gave me the chance to work and interact with some of the best Data Scientists. The learning curve was steep and sometimes, the going did get tough, but by the end of it all, I realized that Data Science was the field which I was passionate about.
Currently, I am working as an Intern at Crowe, Dubai, and as a part of this internship, I have had the opportunity to work on creating databases for the company's various portals, writing triggers, and functions for automating certain tasks such as the scheduling of meetings and storage of documents.
All these experiences so far, have given me an exposure on working with all aspects of the data science spectrum such as data collection, storage, retrieval, analytics, and prediction. Each and every single one of these aspects have improved my skillset and provided me with a deeper understanding of what Data Science is actually about.
In a world surrounded by petabytes of data spanning diverse fields, the fact that I could extract useful information, analyze it and provide people with recommendations or suggestions which could improve their lives is what makes me want to pursue a career in this field. And, with the help of XXXXX University's Data Science program, I could certainly polish and sharpen my skills while being surrounded by some of the world's best professors, researchers and students, and eventually become the best at what I do.
The XXXXX University's program is one which is a perfect fit for me as it would provide me with the flexibility of choosing the courses which I want to learn more about, and at the same time, use the University's strong alumni network and location to meet and interact with professionals with whom I could, potentially, collaborate, research, and work with on projects which could make the world a better place.