Dwisha Mehta Email & Phone Number

Automated Model Risk Management scripts to perform data extraction from the database and enhanced the code for the future quarterly reportsLearned a new library named Qztable used by the developers at BofA, expanded Python skillset, data visualization skills, and learned LaTeX for reports documentation Optimized the script, which resulted in a significant reduction in operational runtime; enhanced user interface design, increased scalability and robustness; improved it’s performance in handling large datasets.

Reviewed the customer and transaction data of Sprocket Central Pty LTD using Excel Pivot Tables, Filters, Functions, and the Standard Data Quality Dimensions, resulting in improved data quality and accuracy.Designed and delivered a comprehensive PowerPoint presentation outlining the approaches to boost business by analyzing customer datasets, identifying customer trends and behaviors, and following the 3 phases of Data Exploration, Model Development, and Interpretation. This resulted in increased client satisfaction and business growth.Utilized Tableau to demonstrate, visualize, and develop an interactive dashboard that presented the underlying data trends, identified the customer segments with the highest customer value, and recommended a marketing and growth strategy for the client. This resulted in improved client retention and increased revenue for the client.

Tesla Stock Market Prediction – Machine Learning & NLP Project Working on building a time-series machine learning model (LSTM model) in Python to predict the Tesla Stock prices using sentiment analysis of news headlines; Analyzing trends and patterns in the stock market data to gain insights about possible future trends. Complete text analysis, which includes text cleaning, data preprocessing techniques such as Stemming, Lemmatization, and Removal of words that are manually prepared for domain purposes.Product Sales Analysis – Tableau Project Analyzing huge real-world data of the company products and sales and giving meaningful insights using Exploratory Data Analysis (EDA) and Predictive Analytics.Demonstrated strong data analytics skills to gain insights from the data to maximize the retail store’s sales and profits; Presented findings and recommendations to improve the business using Tableau.

Participated in all the phases of data acquisition, data cleaning, developing models, validation, and visualization to deliver data science solutions Yelp Business Reviews Prediction – NLP Project ● Performed NLP classification task and text preprocessing in Python to predict the yelp ratings for a particular business ● Explored the data using different data visualization tools and libraries, including Matplolib and Seaborn ● Performed complete data cleaning, text analysis, prediction, and model evaluation ● Text analysis using the pipeline to perform data preprocessing techniques (Vectorization, TF-IDF Transformer) Loan Approval Prediction – Deep Learning Project ● Created a prediction model to predict loan status, taking into account various attributes, whether a person will be able to pay back the loan or not● Complete data cleaning process such as dropping insignificant variables, removing or filling in missing values, filtering, converting categorical variables, feature engineering, formatting data, and interactive plotting visualizations ● Complete neural network model using deep learning techniques (activation function, loss function, gradient descent, Optimization, Backpropagation, Early stopping, Dropout method)