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Data Science Machine Learning

Arlington, VA
February 11, 2024

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Swathi Murali Srinivasan

Arlington, VA 408-***-**** LinkedIn Github EDUCATION

The George Washington University, Washington, DC August 2023 - May 2025 Master of Science, Data Science

Coursework: Introduction to Data Science, Introduction to Data Mining, Data Warehousing Visvesvaraya Technological University (VTU), Karnataka, India June 2016 - August 2020 Bachelor of Engineering, Computer Science & Engineering Coursework: Database Management Systems, Machine Learning, Statistics, Artificial Intelligence, Operations Research TECHNICAL SKILLS

Programming & Web Development: Python (Numpy, Scikit-Learn, Pandas, Matplotlib, Seaborn), R, SQL, HTML, CSS, JavaScript, ReactJS, Flask

Machine Learning & Data Analysis: Predictive Modeling, Statistical Analysis, Regression, Classification, Clustering Algorithms, Decision Trees, Exploratory Data Analysis, Basic Time Series Analysis Development Tools & Database Management: Jupyter Notebook, Google Colab, R Studio, Visual Studio Code, Git, GitHub, Jira, MySQL, MongoDB, Neo4J

Visualization & Reporting: MS Excel, Qlik, Tableau TECHNICAL PROJECTS

Customer Segmentation and Analysis of Starbucks Customer Data Spearheaded advanced customer segmentation of 1+ million Starbucks data entries using k-means, logistic regression, decision trees, SVM, achieving 89% model accuracy. Predictive Analysis of Anime Ratings

Utilized XGBoost regression on anime data to predict user ratings, achieving a Mean Absolute Error of 0.22, highlighting the model's accuracy in identifying key factors like studio and release season. Comparative Performance Analysis: MySQL vs. MongoDB in Database Systems Collaboratively conducted a comparative study with a 3-member team on MySQL vs. MongoDB, unveiling a 20% boost in MySQL's query efficiency and 25% enhanced scalability in MongoDB, pivotal in strategic database decisions. Predictive Analysis of Students' Academic Performance Engineered a predictive model using Python, NumPy, Pandas, XGBoost, and Flask, accurately forecasting students' CGPA and identifying at-risk students with 85% precision, enhancing early intervention strategies. Games Database Management System

Designed and implemented a desktop app using NetBeans (Java) and integrated it with a MySQL database, resulting in a 30% improvement in game search efficiency and a 20% reduction in data update times, enhancing user experience. PROFESSIONAL EXPERIENCE

UI Developer 2, Bottomline Technologies, Bangalore, India September 2022 – July 2023

● Executed a collaborative migration project from Backbone Marionette to ReactJS, resulting in a 30% boost in product performance and enhanced user satisfaction.

● Identified and fixed over 50 major bugs, resulting in a 20% increase in product stability and a significant reduction in customer complaints.

Software Engineer, Bottomline Technologies, Bangalore, India August 2020 – September 2022

● Mentored new hires in front-end development best practices, enhancing team integration and boosting productivity by 30% within their initial month.

● Developed a new "Link Builder" feature using ReactJS and React Router, contributing to a 30% rise in user engagement and significantly improving the overall product experience.

● Streamlined form generation by integrating JSON data from the backend API in collaboration with the server-side lead, resulting in a 30% reduction in development time. Data Science Intern, Pluto7, Bangalore, India January 2020 – March 2020

● Improved data analysis accuracy by 35% by implementing advanced data cleaning techniques on a large dataset.

● Utilized univariate and multivariate time series forecasting techniques to refine real-time project outcome predictions, yielding a 20% improvement in forecast accuracy.

Data Science Research Intern, e-Sutra Chronicles (contineo), Bangalore, India June 2019 – August 2019

● Investigated and assessed AI platforms and frameworks, leading to a 20% advancement in problem-solving efficiency and optimizing tool selection for specific use cases.

● Implemented a mini project using Google Colab and TensorFlow/Keras, facilitating a 20% enhancement in the team's understanding of deep learning techniques.

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