Vatsal Gujarati

•Conduct big data analyses for Customer Insight in Body, Interior, and Exterior domains •Analyze vehicle-generated data using tools like Athena, AWS Glue, AWS QuickSight, and Palantir, while developing analysis logics in SQL and PySpark •Update and extend Python scripts, utilizing Jira and Confluence for project management and documentation •Stepped up to lead and supervise the team during key projects, ensuring successful execution and delivery

- Built and fine-tuned regression models to predict sales, boosting accuracy by 15% - Cleaned and analyzed large datasets using Python libraries (Pandas, NumPy) - Implemented a neural network for image classification with TensorFlow, increasing accuracy by 20% - Developed interactive dashboards in Tableau and prepared reports for stakeholders

•Developed robust models for data analysis and prediction tasks using Python and R programming languages •Implemented various machine learning algorithms using libraries such as NumPy, Pandas, Scipy, TensorFlow, Keras, PyTorch, and Scikit-learn •Deployed machine learning models on cloud platforms like AWS and Google Cloud Platform (GCP) •Built predictive models with machine learning (regression, clustering, random forest) to optimize forecasting and problem-solving

Current grade: 2.4 Courses: Machine Learning and Data mining Data Science Web Science Big Data Artificial Intelligence Engineering Web and Data-intensive Systems Pattern Recognition Web information Retrieval Semantic Web Graph Theory Network Theory and Dynamic Systems Optimization

Grade: 1.89 GPA Courses: Python Programming C, C++, C#, .Net Data mining Software Engineering Data Structure Advanced Java Database Management System Web Technology Computer Network Operating System Analysis and Design of Algorithms Advanced Engineering Mathematics Numerical and Statistical Methods for Computer Engineering