About

Anitha Karunakaran is a data scientist with 3 years of experience in data pre-processing, applying and building machine learning models, drawing business insights utilizing R, Python, and generating reports in Tableau. She holds knowledge in predictive modeling (Regression, Decision tree, KNN), and statistical analysis (regression analysis, hypothesis testing). With strong proficiency in problem-solving, team collaboration & communication, she is seeking future opportunities in a data-driven organization. Currently, Anitha is a Graduate Student at Georgia State University - J.Mack Robinson College of Business pursuing an MS in Data Science and Analytics. She is also working as a Data Science Intern at LexisNexis Risk Solutions Group where she is responsible for developing machine learning models to solve business problems. In her previous role as a Project Experience at Truist, Anitha automated data extraction through web scraping leveraging Selenium web-driver, gathered mortgage-related customer reviews from BankRate.com, and applied data cleaning and feature extraction steps in Python utilizing packages Scikit-Learn, Natural Language Toolkit. She also accomplished sentimental analysis on content utilizing TextBlob, Vader, and applied supervised learning models Naive Bayes, Logistic Regression. Anitha has also worked as a Graduate Research Assistant at Georgia State University - J. Mack Robinson College of Business where she was responsible for analyzing data and generating insights for research projects. Anitha holds a Master's degree in Data Science and Analytics from Georgia State University, a Master's degree in Theoretical Computer Science from PSG College of Technology, and Intermediate School Education from Sri Chaitanya Junior Kalasala. Anitha's tech stack includes Research Scientist, ML, Data Scientist, Python, test, Supervised Learning, Naive Bayes, Web, Selenium, Scikit. With 4.02 years of relevant experience, she is a highly skilled data scientist with a passion for solving complex business problems.