Hi, I am Shubham Jain, a graduate student at Heinz College, Carnegie Mellon University, pursuing my Masters in Information Systems Management. Before coming to CMU, I was working as a software developer at Philips HealthCare Systems. I strive to develop things that can bring change to society by transforming data into decisions. My greatest ability is to stay true to my work. The fondness of analysis and prediction amplified my interest in the field of data science driving me to explore more in this domain and gain thorough in-depth knowledge of several tools, techniques, and technologies. Over the next few years, I wish to not only understand the technical aspects of data science but also to ensure the ethical style of storytelling with data.
Speaking of a few fun facts about me, I am really passionate about football and a huge fan of Cristiano Ronaldo.
Interested areas – Data Analysis, Data Visualization, Machine Learning, Natural Language Processing, and Software Application Development.
I worked as a software developer and have had the opportunity to render my services as a part of the CoreServices team and work on the development of applications to provide software installation framework for different hardware platforms, OS automation suite engine, backup and restore infrastructure using.net framework the windows, to name a few.
My role as an intern was to develop an automation suite that could completely deploy the customized operating systems and configure the MRI health systems with required application software. It was a huge cost saver to Philips as it brought down the time of deployment from 14 hours to 4 hours. For the stint of 6 months at Philips, I was also responsible to improve the code quality of the MR codebase without hampering the actual code flow that required extensive code analysis and rigorous testing to attain the best performance and efficiency.
Data Analytics /
This data can also prove useful to predict the daily or weekly or monthly or annual traffic that’s going to accumulate on the borders so that the authorities can be aware of the number beforehand and take necessary actions if required.
Github Code
Data Analytics /
Performed analysis on approximately 8M rows of data, of an existing eCommerce grocery store Instacart and identified the most relevant features to predict the customers’ next order items.
Github Code
Data Analytics /
The dataset contains five year’s worth of H-1B petitions, with approximately 3 million records overall. Identified the factors that can help understand the reasons behind a visa application getting rejected or accepted.
Github Code
Data Analytics /
Flight ticket prices can be something hard to guess, today we might see a price, check out the price of the same flight tomorrow, it will be a different story. This data can also prove useful to predict the fare of a flight given details such as source, destination, time of the journey, and various preferences of a passenger.
Github Code
Data Analytics /
Identified the characteristics of a person who is most likely to suffer from certain cardiovascular events using data visualization and feature engineering using the provided by UCI.
Github Code
Data Analytics /
This data set consists of placement data of students on the campus. It includes various features such as secondary and higher secondary school percentages and specialization. Identified the characteristics that can help a student to get hired by a company.
Github Code
