● Working as a Data Scientist on projects which involve utilization of neural networking, machine learning and deep learning algorithm for the analysis of the customer data to improve company profit. Presently, developing a reverse image search engine of more than 200k images, applying NLP techniques for product recommendation. ● Work involves the application of Tools: Python, TensorFlow, Kera’s, Tableau, R ● Platform: Google Cloud, Anaconda, AWS Sage makerSentiment Analysis using NLP (Python, Tableau) :● From the given Yelp reviews of TS Restaurants, located in Hawaii, the objective was to extract the aspects and opinion indicators using Text blob, NLTK, and Spacy libraries. Post data preprocessing, the polarity and subjectivity of the sentences were determined using a text blob.● Extraction of N-Grams (Bi-Grams and Tri-Grams) using Spacy and their corresponding sentiments.● Analyze product reviews at scale through an algorithm that can identify key themes and enable buyers, suppliers, and quality inspectors to take actionable decisions around product quality risk mitigation and improve customer satisfaction Done Kmart sentiment analysis with real data of K-Mart as a part of Applied Research Experience using Machine Learning and NLP.● The machine learning system was able to learn from all the positive, neutral, and negative reviews, and fine-tune the algorithm to avoid bias sentiments.TS Restaurant:● Applied time series, neural networking, and machine learning tools such as LSTM, cluster analysis, and SARIMA, SARIMAX models to compare TS restaurant chain with their competitors concerning trend, seasonality, and forecast to improve the business and provide insights. ● The data obtained was from social media websites. The sentiment analysis of the reviews was also performed. Work is submitted for publication. Tools: Python: TensorFlow, Kera’s, Tableau.