GERSHON JOSEPH

ad17vp@r.postjobfree.com

954-***-****

United States / Texas

Kaggle ID: https://www.kaggle.com/gershonjoseph

GitHub ID: https://gist.github.com/shondy1991

LinkedIn ID: https://www.linkedin.com/in/gershon-j-617b0443 Profile Summary

Data enthusiast with a strong background in tool development and supporting testers. Committed to expanding skills through ongoing pursuit of AIML courses. Driven by a passion for excellence and a proactive approach to learning. Eager to contribute expertise to diverse projects, with a keen focus on continuous growth and exploration. Academic Projects

https://eportfolio.mygreatlearning.com/gershon-joseph Project - 1

LINEAR REGRESSION – Dynamic Pricing Model – Retail Build a dynamic pricing model for a used and refurbished devices seller using linear regression and identify key factors. Analyzed dataset, built a linear regression model for resale price, and identified key factors that significantly influenced the price prediction. The model explained ~84% of the variation in the data and predicts the normalized used price within +/- 4.5%.

Project - 2

BUSINESS STATISTICS - A/B Testing – Website Optimization Utilized statistical analysis, a/b testing, and visualization to demonstrate the effectiveness of a new landing page of an online news portal (E-news Express) to gather new subscribers. The total numbers of users in the old and new landing pages were 50 and 50, however, users spent more time on the new landing page than the old landing page. There was enough statistical evidence (p-value of 0.0080 at 5% level of significance) to conclude that the conversion rate for the new page was greater than the conversion rate for the old page.

Project - 3

UNSUPERVISED LEARNING – K-means Clustering, Hierarchical Clustering, Cluster Profiling, & PCA

Built an optimized (diversified) portfolio by analyzing and clustering stocks based on financial attributes.

Analyzed stock data for 340 companies, grouped the stocks into 6 clusters using both K- Means and Hierarchical clustering analysis techniques. Identified similar and dissimilar characteristics within attribute data points (price, volatility, industry sector,

and typical financial indicators) by performing EDA, scaling the data, and correlating features. Provided insights about the characteristics of

each group which helped develop an optimized portfolio for clients with custom risk-return profiles.

Skills:

• Statistics and Data

Visualization:

- Descriptive

- Statistical

- Predictive

Analytics

- Seaborn

- Matplotlib

• Machine Learning:

- Classification and

Regression

Algorithms

- Statistical

Inference

- Exploratory Data

Analysis

- Clustering

Techniques

- PCA

- Recommendation

Systems

- Hyperparameter

Tuning

- Feature Selection

- Scikit-Learn

- NumPy

- Pandas

- XGBoost

• Deep Learning:

- Neural Networks

- Computer Vision

- Image Recognition

- Natural Language

Processing

- Web Scraping

- Tensorflow

- Keras

• Languages:

- Python

- SQL(MySQL)

Education

Post Graduate Program in Data Science & Business Analytics University of Texas at Austin McCombs School of Business, Austin, TX Graduation Year: 2023

GPA: 3.9 / 4.0 Artificial

Certifications

Intelligence on Cloud

Introduction to SQL

Associates of Science in Graphic Design

Broward College, Ft. Lauderdale, FL

Graduation Year: 2016

GPA: 3.0 / 4.0

• Other

software/Tools:

- AWS, Docker

- Jupyter Notebook

- Google Collab

- R Studio

- MySQL

- Workbench

- Excel

- Anaconda

- VSCode

- Spyder, Weka

- Zoomph

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