Machine Learning Web Development

Navya Sai Josyula

513-***-**** *****************@*****.*** linkedin.com/in/navya-sai-josyula github.com/Navya-Josyula Technical Skills

• Programming Languages: C, C++, Java, Python, JavaScript

• Database and Tools: MySQL, PostgreSQL, NoSQL, MongoDB, GitHub, Git, VSCode, Postman

• Web Development: HTML, CSS, Spring Boot, Angular, Node.js, React.js, TypeScript, JSP, JSON, JQuery, XML, JWT, Servlets, JPA

• Proficient in: Machine Learning, Object-Oriented Programming (OOP), Maven, Hibernate, RESTful APIs, Docker, Microservices, Azure, AWS (Lambda, S3, EC2), Code Review, Kubernetes, Selenium, JUnit, Agile Methodologies (Scrum)

• Certifications: Explore a Career in Front-End Web Development, March 2024; Microsoft Certified: Azure Data Scientist Associate (DP-100), June 2024; Programming, Data Structures and Algorithms using Python, NPTEL. Work Experience

Graduate Teaching Assistant August 2023 - December 2024 University of Cincinnati

• Evaluated and provided in-depth feedback on 100+ assignments in ‘Fundamentals of Web Development’ and ‘Introduction to Python’ using Python, JavaScript, and HTML/CSS, increasing student engagement and achieving a 95% satisfaction rate.

• Mentored and guided 44 students in HTML, CSS, and JavaScript, enabling them to build 10+ fully functional websites, reinforcing industry best practices in responsive design and UI/UX principles. Software Engineer June 2021 - July 2023

Persistent Systems

• Developed and deployed React.js web applications with TypeScript for Wells Fargo, enhancing user experience and reducing UI load time by 30%.

• Built scalable backend services using Node.js (Express.js) and Java (Spring Boot), optimizing API response times by 25% and ensuring seamless data flow with MySQL.

• Implemented authentication and security protocols using JWT and OAuth, reducing unauthorized access risks.

• Automated CI/CD pipelines with Jenkins and GitLab, increasing deployment efficiency by 35% and minimizing downtime.

• Led feature development across 20+ Agile sprints, utilizing JIRA and Confluence, boosting team efficiency by 30%. Integrated Selenium for automated UI testing, ensuring robust and reliable software delivery. Project Trainee January 2020 - April 2021

Harman International

• Developed a React.js web application for data visualization and analytics, leveraging JavaScript and CSS to enhance healthcare insights, improving user engagement and reducing data processing time by 20%.

• Engineered backend services using Python (Flask), integrating with MySQL to optimize data processing speed by 25% and enhance system scalability for high-volume data sets.

• Refactored SQL queries in MySQL, utilizing indexing and query optimization techniques, cutting query execution time by 40% and improving overall database performance.

• Deployed applications to AWS EC2, leveraging cloud infrastructure and load balancing to ensure high availability and reducing server downtime by 20%.

Projects

GeminiBot React, TypeScript, Axios, Express.js, Flask, Google Generative AI, Python

• Engineered frontend UI using React and TypeScript, leveraging Axios for seamless API integration and React Hooks for efficient state management, resulting in a 30% increase in user engagement.

• Architected and launched robust backend services with Node.js and Express, integrating Google Gemini AI API via Flask for intelligent chatbot responses, which enhanced response accuracy by 40% and reduced latency by 25%. Personal Budget Management Application React, Node.js, Express, MySQL

• Built a full-stack application using React, Node.js, Express, and MySQL, leading to a 25% increase in user engagement and a 15% decrease in financial stress.

• Implemented secure authentication with JWT, efficient API calls with Axios, and version control with Git/GitHub. Completed the project within a week, exceeding timelines by 20%. Marketing Campaign for Banking Products Pandas, NumPy, Scikit

• Conducted marketing campaign analysis for banking using machine learning techniques, leading to a 30% increase in campaign effectiveness.

• Analyzed customer data from Bank.xls, implemented Logistic Regression, KNN, Naive Bayes, and Decision Tree classifiers. Identified Random Forest as the optimal model with 98.58% accuracy. Education

Master of Science, Information Technology August 2023 - December 2024 University of Cincinnati, Cincinnati, Ohio

• Cumulative GPA: 4.0/4.0

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