Adam Ezzat Page * adtwfx@r.postjobfree.com

ADAM EZZAT

***** **** **** ****, ********* California 95014

408-***-****

adtwfx@r.postjobfree.com

https://www.linkedin.com/in/adamezzat/

Ability to analyze data and extract useful information to meet business goals using machine and Deep learning in data analysis applications for future planning and forecasting. I have 2+ years experience in the industry as Data Analyst and valuable experience in SQL, Python, and Machine learning libraries and development environment. In the data science area, I had experience in Data Collection, data Cleansing, Analyzing and Processing the data to extract useful information. I have a certificate in Data Science (1.5 years) from Springboard with major in Deep/Machine Learning. Relevant projects implementation posted on GitHub:

• Neural Networks: using logistic regression for classification. Scan images and use logistic regression to determine if that image is for a cat [1].

• K-means Clustering: divide a county into a set of clusters for a given population age and identify the centroid, radius, and population for each cluster to recommend the appropriate location for a Sport event [2].

• Association rules: knowing the original and sales price for a set of used cars, identify the features that helped in least depreciation for a car price [3].

• Naïve Bayes: perform NLP to identify positive and negative sentiments from a movie review text [4].

• NLP/Sentiment Analysis: using Tensor Flow and NLTK: figuring out the most positive and most negative sentiments associated with a set of Airlines based on a dataset from Kaggle [5].

• NLP/Sentiment Analysis: Used Tweepy to Crawl/Scrape Twitter tweets for data about multiple Airlines and customers input and generate the output as CSV file. Then take the CSV file as input to the above NLP Sentiment Analysis application to find out how customers think of an Airline [6].

• Dashboard using Plotly/Dash platform to present the above sentiment analysis in different dashboard formats including comparing customer input on two or more airlines.

• R-Programming - Sales Analysis: Used the tidyverse package to merge three dataframes (bikes, bike stores, and order lines) together using relevant columns that existed between the dataframes. Then wrangled the data using the dplyr library function mutate to create a column to show the revenue and separate to change a column of location showing state and city into two separate columns of state and other being city, format the data to make it look more presentable and then finally used ggplot to visualize the sales [7].

• Certificate in Deep Learning specialization including Sequence Models: and their applications including speech recognition, music synthesis, chatbots as well as applying RNNs (Recurrent Neural Networks) to character level language models, creating tokenizers and different transformer models to solve various kinds of NLP problems

• Familiar with relevant Machine Learning tools and libraries including visualization like: Tensorflow, Keras, and Pytorch, Altair, Plotly, and others [8].

• Familiar with SQL and parallel processing platforms like Databricks-Lakehouse over Spark to build binary classification models [9].

• Familiar with Statistical Analysis including regression analysis, Plotting, Gaussian distribution, variance, standard deviation [10].

• Familiar with ETL tools including Data Wrangling, Beautiful Soup: scarping information from Kelly Blue Book to identify missing data [11].

• Multiple JSON projects: load Json data set and used Pythion to explore <Key : Value> pairs [12]. Effective communicator and comfortable working with colleagues and across organizational levels. In addition, I have an MBA, St Mary’s College with major in Business Analytics and Technical Marketing and BS in Science from Santa Clara University. Have business experience through three internships and an IT support job in the Business school during my college years and my role at Big Data Insights, where I research product planning and communicate with team members to produce recommendations to ensure that our product will be competitive. Earlier academic projects at Santa Clara University included: designing a website for laptop and accessory purchasing leveraging “what-if” analytics to provide purchase recommendations based on hardware configuration and budget.

• Data Science • Python Programing • Java Programming, SQL Programing • Cost / Benefit Analysis • Market Analysis

• CRM • Product and Internet Marketing • Technical Support • Consulting • Process Improvement • Client Relations • Customer Service • social media.

Adam Ezzat Page 2 adtwfx@r.postjobfree.com

Amazon, Lab126, Lab Engineer, Sunnyvale, California • 9/2021 – Current: Using Python in my work. Understand the business problem, Data Collection from different audio devices, cleaning the data, and validating the devices quality. Evaluate emerging technologies and determine applicability to our current and future projects. In addition, I do miscellaneous tasks including:

• Run and debug MATLAB scripts.

• Creating dashboards for virtualization in the context of data collection. BIG DATA INSIGHTS • Cupertino, California • 8/2019 – 8/2021: Big Data in Distributed Cloud: Data Analyst:

Performed research analysis to improve response time in a distributed system. The goal is to enable the platform to migrate the data transparently to optimize user access time. The model is based on Machine learning, and I worked with the development team in the implementation. I did a competitive analysis to ensure that our product is competitive. LCI / VERIRISK • Burlingame, California • 12/2018 – 8/2019: Bankruptcy Management Solutions. Operations Analyst

Created SQL programs to modify database tables. Utilized proprietary software to audit client records and identify potential issues. Collaborated with teams using MS Excel and pivot tables. QUEST EXCHANGE • San Francisco, California • Summer 2018 High school exchange programs for International and American students. Summer Internship

Assisted Content Generation and Digital Marketing Departments in their marketing campaigns. Used Mail Chimp, Google Adwords, Adobe Illustrator, and Photoshop.

STATE INSURANCE COMPENSATION FUND • Pleasanton, California • 2/2016 – 8/2016 Workers' compensation insurer for the State of California, Research Consultant and Student Intern

Researched WBE, MBE, SDVOSB certification opportunities for diversity specialist. Researched potential clients utilizing Oracle Financial and Ariba to create employee spending reports. MERRILL LYNCH • Berkeley, California • 9/2012 – 12/2012 Investing and wealth management division of Bank of America (Fall Intern / Wealth Management Group): Performed customer relationship research with Salesforce CRM system applications analyzing client’s portfolio investments. Reviewed the financial data and prepared spreadsheets of top performing investments by asset class. Researched customers’ accounts/portfolios and market trends to predict if current portfolio meets the customer goals. SANTA CLARA UNIVERSITY • Santa Clara, California • 1/2011 – 8/2012 (Private Jesuit University). Information Technology Assistant / Business School Addressed software issues providing technical services & support. Maintained and updated Business School hardware. SILICON VALLEY UNIVERSITY • San Jose, California • 7/2011 – 9/2011 (Private, non-profit educational University). Student Marketing Intern

Identified and implemented a Go-to-Market strategy to enhance US students’ recruitment. Communicated with local community colleges, local employers, local public high schools, and social media. The University adopted my report. EDUCATION

• Data Science Certificate with major in Machine Learning, Springboard.com (1.5 years) completed in November 2021. Heavy hands-on programming using Jupyter Notebook and Google Colab

(IDE). Topics covered include Python on Web scrapping, Visualization, Statistics, Machine learning, and deep learning. Examples of my projects are posted on GitHub home page https://github.com/sethorus30.

• Master of Business Administration (MBA) in Business Analytics and Marketing (GPA: 3.75) Saint Mary's College of California, Moraga, California

• Bachelor of Science in Economics

Santa Clara University, Santa Clara, California

• PROFESSIONAL TRAINING

o Online training courses such as: https://www.udemy.com/machinelearning/ Adam Ezzat Page 3 adtwfx@r.postjobfree.com

o Completed certified ten data camp courses: data types for data science in Python, Python data science Toolbox (part-I, part-II, Introduction to data visualization in Python, Pandas Foundations, Data Cleaning in Python, Merging DataFrames with Pandas, Manipulating DataFrames with Pandas, and Introduction & Intermediate-level to Importing Data in Python.

o DataCamp Certificate, Introduction to Statistics in R o Querying Microsoft SQL Server 2012, Lynda.com Certificate o Technical Writing for Reports, Lynda.com Certificate o 365 Data Science Certificate, Data cleaning and preprocessing with Pandas o 365 Data Science Certificate, Data Analysis with Excel Pivot Tables o Coursera Certificate, Neural Networks and Deep Learning o Coursera Certificate, Structuring Machine Learning Projects o Business Science University Certificates, Data Science for Business, Parts I & II (R)

• COMPUTER Tools:

o MS Office Suite, SQL, Python, R, Java, Databricks/Spark, Tableau, Power BI, Sklearn, Pandas, Tensorflow, Pytorch, Keras, Plotly, Google Colab (IDE), Jupyter Notebook, Google Adwords, Mail Chimp, Adobe Illustrator, and Photoshop.

Background:

• US Citizen.

GitHub References:

1. Neural Networks using logistic regression:

https://github.com/sethorus30/Neural_Netowrks/blob/main/Logistic_Regression_with_a_Neural_Network_mindset.ipynb 2. Data Science Clustering: https://github.com/sethorus30/Data-Science---item1-K-means-Clustering 3. Data Science Association Rules: https://github.com/sethorus30/Data-Science---item2-Association-Rules 4. Data Science Naïve Bayes: https://github.com/sethorus30/Data-Science item4-Naive-Bayes 5. Data Science NLP Sentiment Analysis using Deep Learning: https://github.com/sethorus30/Data-Science---item5- Deep-Learning

6. NLP/Sentiment Analysis using Tweepy: https://github.com/sethorus30/Data- Science/blob/master/Tweepy_Deeplearning_NLP_capstone.ipynb 7. R-Programming - Sales Analysis: https://github.com/sethorus30/R_projects/blob/main/02_sales_analysis.R 8. Data Science tools and libraries: https://github.com/sethorus30/Tools-and-Libraries-1 9. SQL and Parallel Processing Platforms: https://github.com/sethorus30/SQL-projects-1 10. Statistical Analysis: https://github.com/sethorus30/Statistical-Analysis-1 11. ETL: https://github.com/sethorus30/ETL1

12. JSON Projects: https://github.com/sethorus30/Jason-Projects-1

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