Aishwarya Vantipuli is a data science candidate at Northeastern University with a master's degree in data science. She has experience in machine learning techniques like regression, clustering, and neural networks. Her academic projects include analyzing suicide rates, text mining political speeches, and building a restaurant review application. She has worked as a data analyst applying analytics to improve business strategies. Personal projects include image recognition and exploring education data.

1. AISHWARYA VANTIPULI
Boston, MA - 02120 | +1(217)-695-4626 | email: Vantipuli.a@husky.neu.edu. | LinkedIn | GitHub
Available: From January 2020
EDUCATION_______________________________________________________________________________________________
Northeastern University, Khoury College of Computer Sciences, Boston, MA Jan 2019 – Dec 2020
Candidate for a Master of Science in Data Science (MSDS)
• Related Courses: Supervised Machine Learning, Unsupervised Machine Learning, Data Structures and Algorithms.
Jawaharlal Nehru Technological University, Hyderabad, India Sept 2013 – May 2018
Bachelor of Technology, Information Technology (IT)
• Related Courses: Programming in C and Java, Artificial Intelligence, Information Retrieval Systems, DBMS.
TECHNICAL KNOWLEDGE_________________________________________________________________________________
Programming Languages : R, Python, SQL, C, Java
Libraries/Packages: Numpy, Pandas, Scikit-learn, Matplotlib, ggplot2, tidyr, dplyr
Database Technologies : My SQL, Oracle
IDE/Tools : RStudio, Jupyter, Eclipse, Tableau, Advanced Excel, AWS, Google Collab
Analytical Techniques : Regression Techniques, Tree-based models, K-Means Clustering, KNN,
Cross-validation, Text Analytics, SVM, Principal Component Analysis, Bayesian
Analysis.
ACADEMIC PROJECTS_____________________________________________________________________________________
Northeastern University, Boston, MA
• Virginia Transgender Health Initiative Study: Investigated attempted suicide rates among Transgender in comparison to
National average of suicide rates of general US population and factors leading to suicidal tendencies.
• Trump’s Campaign Speeches Data: Examined Trump’s campaign speeches given between June 2015 to November 2016 to
figure out most frequent words and sentiments with text mining and sentiment analysis.
• Reviews of the top 6 companies Data: Generated geo-spatial data for the locations using Google ggmap Package.
Represented best company to work based on ratings and identified on an interactive Map.
• Restaurant Review Database Application: Delivered a data-driven web application that is built on top of relational
model with 100K rows of Data extracted using Yelp API.
• Diabetic Retinopathy Detection: Creating an automated Machine Learning system capable of assigning a score based on
severity scale ranging from (0) No DR to (4) Proliferative DR using Keras.
WORK EXPERIENCE_______________________________________________________________________________________
Younify, Hyderabad, India May 2017 – Dec 2018
Data Analyst
• Collected, cleansed and provided modeling and analyses of structured and unstructured data used for major business
initiatives.
• A 15% reduction in transportation costs, resulting 12% increase in annual savings. Presented data and conclusions to team in
order to improve strategies and operations.
• Proposed Business insights for NISSAN using Instagram Analytics. Data is extracted using Instagram API.
• Utilized MYSQL, data warehousing programs, Tableau and other dashboard/visualization toolsets for data intelligence and
analysis.
PERSONAL PROJECTS______________________________________________________________________________________
• Image Recognition: Attained 99.5% accuracy by training a Convolutional Neural Network (CNN) on MNIST data
predicting Hand written digits through webcam using Open CV
• Boston Housing Data: Created an interactive Tableau dashboard to compare per capita crime rates and its spurious
correlation with distance from Boston employment centers, number of rooms per dwelling and accessibility to highways.
• US Department of Education’s Civil Rights Data: Explored whether Black students received a disproportionate number of
in-school suspensions in contrast to students of other races
CERTIFICATIONS__________________________________________________________________________________________
• Data Analysis with Python – IBM Cognitive Class Jun 2018
• Python for Data Science– Data Camp Aug 2018
• Machine Learning – Coursera Aug 2108