ZALAK BORAD

Motivated Data Analyst eager to apply Data Analysis techniques in Australia. Have professional experience handling customers in a busy cashier role. Demonstrated leadership skills through participation in national government-organized camps, fostering a bold and enthusiastic personality adaptable to various sectors as well as recognized for being calm and highly disciplined, seeking opportunities to contribute skills and passion for data analysis in Australia.

· Successfully built two machine learning models to classify different categories of images using CNN as well as to predict future stock prices using LSTMs. Obtained 98.56% accuracy for image classification task and 96.45% accuracy for stock prices while replicating academic papers.

· Developed a UN dashboard using Plotly and Dash to display GDP, Population, MaritalStatus, Life Expectancy, and Employment Status across different countries. In addition, obtained modelling skills by utilizing historical data from the United Nations website.

· Successfully built statistical learning models using Lasso regularization, Stepwise selection, Logistic regression, and Binary regression to decide whether winning a toss in cricket is important or not using 10 years of Big Bash League Dataset. Drafted professional business reports and virtual presentations to deliver the analysis.

· Successfully built ARIMA and VAR models to predict future Gold Prices by replicating the work of academic papers. 20 years to non-stationary monthly data from Yahoo Finance was utilised to perform analysis in EViews and delivered professional academic report.

· Worked on a Case study to predict the stock prices volatility for everyday traders using machine learning algorithm and statistical models. 24 years of four technology companies’ stock data was sourced from Yahoo Finance with daily frequency. LSTM, Multivariate LSTM, Ensembles using AdaBoost, ARIMA and Multivariate ARIMA were chosen to perform this task. Achieved 68.7% accuracy on LSTM.