Summary
Experience
Data scraping (automated) in Python(object oriented, using BeautifulSoup, Selenium).
Statistical analysis (descriptive), user clustering, data visualization(Python and Power BI).
Creation of a SQL database for Tableau.
Fetched data on a AWS Redshift database using SQL (PostgreSQL), up to 10,000,000 of rows.
Processed, cleaned and formatted various data using NumPy and Pandas.
Visualized data using QuickSight and Python libraries (Seaborn, Matplotlib), created a dashboard.
Implemented a machine learning regression model (random forest) for time series prediction in 3 weeks.
Led a group project (team of 5): leadership, project management, teamwork, task assignment.
Created a collaborative platform for service selling (database management, programming, business plan).
Designed, developed, and implemented a market entry strategy and pitch deck for a new product.
Led efforts to improve efficiencies, increase sales and develop a business strategy in 5 different industries by implementing lean concepts and practices.
Achieved web content annotation and data labeling for Al training, for top tech. companies.
Reviewed/ annotated/ wrote code for existing programs and integrated existing data sets.
Collected, organized, and annotated images from open source projects and corporate projects into a single database for use in information management and analytics platforms.
Projects
A data scraping and data analysis tool to fetch data from Instagram (no API).
The program analyzes the pictures and behaviors of 20,000 users in order to classify their political beliefs, based on their likes on famous French media outlets.
Gathered and analyzed data from over 1000 social media websites to identify the user demographics and patterns of social media usage.
Predicted of the year of birth of 800k users based on a 2Million user dataset, using name, zipcode, gender and email domain achieved a 99.56% accuracy rate.
Algorithms used: clustering (KMeans), regression (Random Forest, Neural Network).
Education
Minor: Statistics, Deep learning, Machine learning, Data analysis
Minor: Mathematics, Algebra, Programming, Statistics
Skills
Programming Languages: Python, SQL, ETEX, R, Bash, PH P, Java, HTML,CSS
Technology: Jupyter, Power BI, SAS, GCP, Visual Studio Code, Wordpress
Libraries: pandas, scikit-learn, TensorFlow, Keras, Sea born
Self Evaluation
Internship
Certifications
Involvement
Coursework
Awards
Publications
Languages