Data Scientist and experienced R&D Engineer with a background in Materials Engineering. Knowledgeable of best practices in research, data collection, and data analysis with hands-on experience. Adept in leading diverse teams, engaging internal and external stakeholders, and implementing process innovations.
Popular businesses, especially ones that offer mutiple products and services, receive large volume of customer feedback in the form of text reviews. Listening to such feedback is essential for a business to succeed. The aim of this project is to use Natural Language Processing (NLP) to extract and aggregate information at the topic level from large volume of customer reviews. Specifically, text reviews from Amazon were used in this project. The model I developed does the following:
Some techniques and algorithms that went into this work include DistilBERT embeddings, sentence tokenization, HDBSCAN clustering, UMAP, TF-IDF, Latent Dirichlet allocation. As the name suggests, DistilBERT is a distilled version of BERT (Bidirectional Encoder Representations from Transformers). It uses 40% fewer parameters and runs 60% faster than BERT, all the while preserving over 95% of BERT's performance. project link
The problem can be broken down as follows:
The goal of the project is to build a model to automate this classification process. The two subreddits that were selected are /r/buildapc and /r/buildapcforme: both based on advising people who want to build their own PC. E.g. recommending parts that are compatible. project link
This is a hypothetical case. Our client, who is an entrepreneur, wants to open an independent coffee shop in Toronto. The goal of this project is to use exploratory data analysis and machine learning to recommend a list of neighborhoods best suited for the purpose. Following factors were considered in making the recommendations:
In 2018 alone, there were 228,047 car accidents in New York City. The goal of the project is to identify high risk factors within NYC traffic. The final deliverable is a report that:
Perform detailed exploratory analysis of the landscape of college entrance testing in the United States. Use results from the analysis to provide recommendations for what CollegeBoard needs to do to increase participation in SAT. project link
New York City has one of the most competitive and expensive real estate in the country. As to be expected, a large portion of the businesses and homes are leased properties. High population density, lack of space for horizontal growth and extensive vertical growth make evictions an unfortunate reality for residents of the city. The goal is exploratory analysis of residents' household income, their level of education and prevalence of certain types of crime in various neighborhoods and how distribution of such factors relate to distribution of evictions per capita.
This study focuses solely on residential properties and their renters. project link
Completed a full-time intensive Data Science program. Gained hands-on experience analyzing large real-world datasets and modeling them using various machine learning algorithms. I also added to my experience in exploratory data analysis and translating data to meaningful stories. Here are couple project highlights:
Led corporate research and development, including creating mass balance models and furnace feeds to improve sustainability and enhance production models. Led corporate research and development, including creating mass balance models and furnace feeds to improve sustainability and enhance production models. Here are some highlights from my work at Gopher Resource: