Student

MALAVIKA RAJANALA

# *****************@*****.*** 551-***-**** Malavika-Rajanala ð Malavika-Rajanala + Jersey city, NJ EDUCATION

Pace University, New York

Master of Science in Computer Science

Sept 2023 - May 2025

GPA - 3.77

Coursework:Advanced Database Management, Parallel Computing, Internet Computing, Computational Statistics, Deep Learning, Mobile Web and Application Development, Systems, AI. SR Engineering College, Warangal, India

Bachelor of Engineering in Computer Science & Engineering July 2018 - May 2022

GPA - 8.14

Coursework: Data Structures and Algorithms, Machine Learning, Artificial Intelligence, Operating System, NLP, Software Engineering, Object Oriented Programming (OOP).

SKILLS

Programming Languages: Python, C, Java, SQL, PL/SQL, R, HTML, CSS, JavaScript, Jquery, JSON, XML, Typescript. Tools & Softwares: MySQL, PostgreSQL, MongoDB, pgAdmin, AWS(EC2), Microsoft Azure, GCP, Firebase, Docker, Kubernetes, Jira, Jenkins, Microsoft SQL Server, Git, Linux, CI/CD, Github, Android Studio. Libraries & Frameworks: Pandas, NumPy, Matplotlib, Tkinter, Django, Angular, Scikit-learn, TensorFlow, Keras, Seaborn, PyTorch, NodeJS, ReactJS, ExpressJS.

Software Development Life Cycle (SDLC) with experience in Agile methodologies. WORK EXPERIENCE

Advanced Application Engineering Associate

Accenture

Aug 2022 - July 2023

Bengaluru, India

Specialized in Microsoft Azure, deploying and managing scalable, secure, and high-performance cloud solutions. Auto- mated CI/CD pipelines using Azure DevOps and Key Vault, allowing faster and more secure deployments.

Deployed 10+ applications to Azure using Visual Studio, GitHub, and Bitbucket, integrating version control and auto- mated deployment strategies. Continuous integration (CI) and automated testing were implemented, reducing deployment time, minimizing errors, and improving code reliability.

Led cloud migration for 20+ applications to Azure IaaS & PaaS, ensuring a seamless transition with minimal down- time. Collaborated with cross-functional teams to optimize resource utilization, improve security measures, and improve application performance.

Advanced App Engineering Associate Trainee

Accenture

May 2022 - July 2022

Bengaluru, India

Completed a hands-on training program at Accenture in cloud computing, gaining experience with AWS and Azure platforms. Learned to deploy, scale, and monitor applications while working with cloud service models such as IaaS, PaaS, and serverless architecture.

Built full-stack web applications using Node.js, TypeScript, and Angular. Focused on back-end service development, strong typing, and the creation of responsive, component-based user interfaces with real-time data handling and routing.

Developed and deployed complete applications to the cloud, integrating front-end and back-end systems. Applied best practices in API development, version control, debugging, and modular coding throughout the training. PROJECTS

Smart Healthcare Management System NodeJs, ReactJs, ExpressJs, PostGreSQL, JWT, AWS, Jenkins, Jira

Developed a full-stack Smart Healthcare System with React.js, Express.js, and PostgreSQL, enhancing patient-doctor interactions with JWT authentication. Integrated real-time scheduling, prescription tracking, and role-based access, improving usability by 60%.

Optimized database queries and API responses, reducing load times by 30%, improving system performance, and en- hancing user experience by 40%

Go-Cart React Native, GCP, Firebase, Clerk

Built a cross-platform shopping app using React Native, with 95% UI responsiveness and Firebase for real-time data. Deployed backend on GCP, improving load performance by 40%.

Implemented secure user authentication using Clerk, enabling 100% session persistence and reducing log-in-related errors by more than 60% through streamlined auth workflows and error handling. Automated attendance system Python, Numpy, Pandas, OpenCV, Haar cascade classifier, LBPH,Tkinter, XML

Developed an automated attendance system using OpenCV face recognition and machine learning, achieving more accu- racy 95% in student identification.

Developed a Tkinter-based GUI application with real-time face tracking, automated attendance marking, and CSV-based record management, improving operational efficiency by 45% and accuracy by 98%. MALAVIKA RAJANALA - Page 1 of 1

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