What is your previous academic experience?
Master of Science in Analytics & Data Science (est. graduation May 2020)
Bachelor of Science in Economics, UNH
Associates of Education, Great Bay Community College
What are your professional goals?
My professional goals are to find a career as a Data Scientist in either Healthcare or Business. To me, both healthcare and business offer interesting problems which I believe Data Science is uniquely positioned to solve.
What projects have you worked on?
I recently worked on a predictive description project for Phone Apps. This project sought to understand if app reviews were an effective vehicle for predicting an apps overall user rating. To answer this question, I used a tokenized dataset of 10,000 app reviews. The major components of this project include:
Outlier Detection Techniques: isolation forest and Mahal Nobis distance; Dimension Reduction Techniques: PCA, Sparse PCA, and T-SNE; Supervised Learning Techniques: K-Nearest Neighbors, Random Forest, Gradient Boosting, and XgBoost, Feature Selection Techniques: gain and weight from XgBoost.
I also worked on an R Shiny project. R Shiny dashboarding and visualizations are incredibly important, for these tools enable us to tell effective and meaningful stories with the data. I chose to build an app that allowed the user to watch and analyze YouTube data from the years 2017 to 2018. This project taught me so much about making shiny applications and showed me some of R Shiny’s strengths and weaknesses. In the end, it was a great tool to learn to help me tell an effective story.
For more details about this project and others, please feel free to visit my website: https://jwr1015.github.io/
How has your time at UNH had an impact?
I found the staff and student body the most valuable thing about the program. The student body is extremely close and this is because we often have to work together in order to solve a problem. Without a doubt this program is intense and in order to be successful, I have come to rely on the consultation of professors and students. The take away is that Data Science is a team sport, and this is because innovation cannot happen within a vacuum. This program also takes a holistic approach to your career development. Some of the career development activities include resume building, seminars, professional presentations, agile training, lean certification, and interview practice.