Navid H.Arani, PhD
About Navid H.Arani, PhD
Navid H. Arani, PhD, is a Data Science Fellow at SharpestMinds and a Teacher Assistant at Ryerson University, with extensive experience in data science and machine learning applications. He holds a PhD in Computational Solid Mechanics and has developed various tools and models to enhance marketing and career advancement in the data science field.
Work at SharpestMinds
Navid H. Arani has been serving as a Data Science Fellow at SharpestMinds since 2020. In this role, he focuses on applying data science techniques to solve real-world problems. His work involves developing tools and models that assist in data-driven decision-making processes. Over the course of his tenure, he has contributed to various projects that leverage machine learning and data analysis.
Teaching Experience at Ryerson University
Navid has been a Teacher Assistant at Ryerson University since 2016. He has supported undergraduate courses in the field of Computational Solid Mechanics. His responsibilities include assisting in the delivery of course content, grading assignments, and providing guidance to students. His experience in academia complements his practical work in data science.
Educational Background
Navid H. Arani holds a Doctor of Philosophy (PhD) in Computational Solid Mechanics from Ryerson University, which he completed from 2016 to 2020. Prior to this, he earned a Master's degree in Computational Mechanics from the University of Tehran from 2012 to 2014. He also holds a Bachelor of Science (B.Sc.) in Mechanical Engineering from the University of Kashan, completed from 2007 to 2012.
Data Science Projects and Tools
Navid has developed several data science projects that demonstrate his expertise in the field. He created an interactive web application using Flask to visualize the predicted success of marketing campaigns based on user input. He also built a review sentiment classifier for food delivery platforms using data from the Google App Store. Additionally, he engineered an end-to-end data pipeline using Selenium, Pandas, and NLTK to predict salaries for over 2000 data science jobs in the United States.
Machine Learning and Data Analysis Contributions
Navid has made significant contributions to machine learning and data analysis. He developed a machine learning model that achieved an AUC of 0.91 for predicting the success of an email marketing campaign. Furthermore, he created an ngram keyword extraction tool to analyze customer concerns through syntactic dependency analysis. He also deployed a career advancement tool that has been utilized by over 700 aspiring data scientists.