Shubham Srivastava

As a recent IT and IT Management graduate with a major in Data Management and Analytics and experience in business analysis, I am seeking a challenging role as a Graduate Research Data Analyst at the University. I aim to apply my technical skills, research skills, and analytical mindset to contribute to innovative research projects while continuing to learn and grow as a professional. With my experience as a teaching assistant, I am confident in my ability to effectively communicate complex concepts and collaborate with colleagues to achieve research goals. My ultimate goal is to utilize my skills and knowledge to make meaningful contributions to the field of data analysis and research.

1. Evaluating Classification Techniques on Different Categories of Datasets, publish in IJSRD in 2018,
The research paper can be accessed at http://ijsrd.com/Article.php?manuscript=IJSRDV6I20166

2. A Study on Consumer Buying Behavior towards Mobile Phones, was published in IJSRD in 2019.
The research paper can be accessed at http://ijsrd.com/Article.php?manuscript=IJSRDV7I60163

• DATA VISUALISATION PROJECTS: TABLEAU
  Netflix movies and TV Shows Analysis of US: Created a Dashboard and visualizations to understand users’ behavior towards TV shows and movies in recent years in different areas. Tools used: Tableau and Gephi.
  Analyzed the US Cybercrime Attack dataset and created a dashboard and multiple visualizations to solve the different problem statements such as Severity of attack, Intensity, etc.
• RECOMMENDATION SYSTEM PROJECTS
  This project is a Content-Based Recommender System that recommends movies to a user by using the similarity of movies and the System used the NLP concept to analyze the sentiments on the reviews given by the user for that movie.
  This project includes Content-based Filtering, Modeling, web scraping, and NLP Sentiment analysis.
  Used techniques Naïve Bayes for sentiment analysis and achieve an f1 score of 90 % and 86% precision.
  Deployed on Heroku: https://moviesrecommend0211.herokuapp.com/
• SENTIMENT ANALYSIS ON TWITTER
  Performed Data Analysis such as collecting and preprocessing a large dataset of tweets from Twitter, and performing feature extraction and text cleaning.
  Used the combination of word embedding input for the Bi-LSTM model to generate a better prediction of sentiments.
  Trained the Bi-LSTM model with the Attention mechanism on the dataset and achieved high accuracy of 91.82% and an F1-measure is 92.39% in identifying the sentiment of tweets as positive, negative, or neutral.
• CAR PRICE PREDICTION
  It is a Kaggle Competition Problem and the focus of this end-to-end ML project is to create a web application using flask and HTML to predict the selling price of a Car.
  Implemented a car price prediction system using Random Forest Regressor and the model was able to provide accurate predictions for a car's market price, enabling users to make informed buying or selling decisions have shown good results for my model with a mean accuracy value of cross-validation is 86%.
  Lastly, Deployed on Heroku: https://carsellingpricepredictions2022.herokuapp.com/
• COTTON DISEASE PREDICTION
  The purpose of this project is to classify the cotton leaf diseases using image classification concepts based on Machine and Deep Learning Models and provide the necessary.
  Collected and preprocessed a dataset of images of cotton leaves affected by different diseases.
  Used techniques are CNN, and LSTM models to solve the problem and achieve an f1 score of 73% and 86% precision.
• AI GUIDED FINANCIAL TRADING
  In this project, we anticipated studying the economic patterns by digging deep into the historical data and market reactions using technical indicators & trading strategies to predict the future direction of the markets.
  For this project, we have tried to improve the performance by Hyperparameter optimization and also by optimizing the trading strategies using the Back-testing strategy to enhance profitability.
  We have implemented a hybrid model of stack layers of CNN & LSTM with attention to the prediction of Forex Prices and achieved an RMSE score of 81%.
• NOKIA REVAMP
  In this Project, we assessed Nokia's situation back in the 1990s till its downfall.
  We worked as a team of consultants where we identified the reasons for their downfall & other external factors.
  We have conducted & implemented SWOT Analysis, Risk, Change, Project and Strategic Management concepts, etc.
  We prepared multiple reports and proposed a solution based on Project management & IT Strategies & Values that were completely based on the stakeholder's needs and requirement

• Quantitative Skills demonstrated by excellence in subjects like Probability and Statistics.
• Communication Skills honed by dealing with project teammates during my masters at Usyd, Internships, and Working at Coles as a Customer Service Executive.
• Teamwork developed by participating in and organizing fests like Ignite Technical fest (UPES), Internships, College Projects & Coles.
• Management Skills refined by my Internship at Ashita Business Solutions where I worked as a Business Analyst & being a project manager in Capstone Project as well as & completed respective management projects at Usyd.
• Time Management Skills honed by delivering services on time while doing an internship and balancing academics, extracurricular activities within the university, and part-time jobs.
• Leadership Skills developed by opting for different Positions of Responsibility in my projects at Usyd.
• Public Speaking Skills displayed by giving the project’s presentation at the university. Moreover, presenting and explaining my strategies and plan to the senior leaders during my internship.