EDUCATION Northeastern University, Boston, MA Jan 2019 – Dec 2020 Candidate for a Master of Science in Data Science (MSDS)
• Related Courses: Supervised and Unsupervised Machine Learning, Natural Language Processing, Algorithms. Jawaharlal Nehru Technological University, Hyderabad, India Sept 2013 – May 2018 Bachelor of Technology, Information Technology (IT)
• Related Courses: Data Structures, Artificial Intelligence, Information Retrieval Systems, DBMS. TECHNICAL KNOWLEDGE Programming Languages : R, Python, SQL, C, Java
Libraries/Packages: Numpy, Pandas, Scikit-learn, tensorflow, Matplotlib, ggplot2, tidyr, dplyr Database Technologies : MySQL, Oracle
Systems : Windows, linux, UNIX
IDE/Tools : RStudio, Jupyter, Eclipse, Tableau, Advanced Excel, Git PROJECTS Trump’s Campaign Speeches Data:
• Examined Trump’s campaign speeches to detect change / shift in speeches since 2016.
• Performed TF-IDF vectorization, Sentiment Analysis using python NLTK framework for gauging overall sentiment.
• Visualized most frequent words using Word Clouds and captured the semantics by evaluating bigrams.
• Built a Recurrent Neural Network and predicted short summaries of speeches using End-End Memory Network and Position Encoding methods with an accuracy of 91.4% Employee Review Analysis:
• Analyzed 10 years of Employee Review Data scrapped from Glass Door, containing textual and Numeric reviews by current and former employees of Top 6 companies.
• Handled missing data using Mean Value Imputation and SMOTE on training data to handle class imbalances
• Generated geo-spatial data for the employee locations using Google ggmap Package and represented them on an interactive World Map using Leaflet Package.
• Developed a Regression model to suggest companies about the areas they can improve based on employee perspective by reporting high and less correlated features.
Diabetic Retinopathy Detection:
• Creating an automatic DR grading system capable of classifying images based on disease pathologies from four severity levels using Image Classification.
• Pre-processed Images using OpenCV, Otsu’s Method by removing Gaussian blur, boundary effects and cropped to isolate the subject. Normalized images to represent pixels between 0 to 1.
• Compared performances of Logistic Regression, Convolutional Neural Network (CNN), KNN and Multi-layer Perceptron (MLP) on High Resolution Retina Images.
• Achieved an accuracy of 93% with MLP. Confusion Matrix, F1 score, ROC and AUC metrics are used to evaluate the model.
Restaurant Review Database Application:
• Delivered a data-driven web application that is built on top of relational model with 100K rows of restaurant data extracted using Yelp API.
• Developed MYSQL and ETL scripts to enable processing of 2-4 GB external data sets into data warehouse using CloverDX Data Integration tool.
• Optimized ETL performance to provide quickest response time possible. WORK EXPERIENCE Younify, Hyderabad, India May 2017 – Dec 2018
• Proposed Business insights for NISSAN using Instagram Analytics. Data is extracted using Instagram API.
• Developed a web crawler to store a list of unique URLs up to a depth of 5, starting from seed, using Beautiful Soup package and checking visited links by applying BFS and DFS algorithms.
• Identified, measured and recommended improvement strategies for Younify across all business areas.
• Built a resume parser for automated extraction of named entities and keywords in job applications for the company.
• Conducted training sessions and mentored new candidates in the team.