Software Engineer

Ankit Malasi

Santa Clara, CA +1-669-***-**** *****.******@*****.*** www.linkedin.com/in/ankit-malasi Summary

Full Stack Software Engineer with 5 years of experience in software development and web development. Adept in developing RESTful APIs, transitioning systems to microservices architecture, and enhancing front-end performance using React. Skilled in optimizing server- side performance. Proficient in Java and JavaScript, with expertise in Agile methodologies and CI/CD pipelines. Seeking to leverage skills to drive innovative software solutions. One area of interest is Distributed Systems. Education

Master of Science in Computer Science Santa Clara University Jun 2024 Relevant Coursework: Design and Analysis of Algorithms, Data Structures, Software Engineering, Operating Systems Bachelor of Technology in Computer Science Govind Ballabh Pant Engineering College Jun 2016 Relevant Coursework: Database Systems, Object Oriented Analysis and Design, Artificial Intelligence, Big Data Skills

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

• Database: MySQL, PostgreSQL, MongoDB, Firebase, Cassandra

• Web Development Tools: HTML, CSS, ReactJS, NodeJS, Spring Boot, AngularJS, Web API, Restful/Rest API, D3 Libraries

• Cloud Technologies: AWS, Apache Hadoop, Apache Spark, Apache Kafka, Docker, Kubernetes

• Tools: Jenkins, Postman, JUnit, GIT, Jira, Tableau, Mercurial Work Experience

Full Stack Software Developer Intern Infinite Options LLC Jul 2023 - Sep 2023

• Built a web application with ReactJS, HTML, CSS, and JavaScript, improving front-end performance by 30%. Enhanced data operation efficiency by 25% through RESTful APIs using Python and SQL.

• Led team collaboration using Git-controlled versioning and agile methodologies, improving project delivery time by 20%.

• Managed tasks and facilitated communication between developers and designers, ensuring cross-platform compatibility. Software Developer Comicsense Oct 2017 – Jul 2022

• Developed a secure online shopping portal with Java/Spring Boot and MongoDB/MySQL, and transformed the UI using HTML, CSS, and React, achieving faster load times through component reusability and driving a 25% increase in traffic.

• Designed and implemented a robust Java-based user authentication system with token-based session management, resulting in a 40% reduction of API attacks and enhancing overall security of the website.

• Transitioned the online shopping portal to a microservices architecture using Java and Spring Boot, enhancing scalability and maintenance, resulting in 30% faster feature updates and better fault isolation.

• Spearheaded the development of RESTful APIs using Java Spring Boot framework and Docker, increasing efficiency by 17%.

• Initiated efforts to deploy a machine learning-based malicious URL detector, enhancing security protocols.

• Managed comprehensive team documentation for major projects, reducing onboarding time for new engineers by 30%.

• Mentored and guided new employees, boosting team efficiency and technical proficiency through personalized training and support.

• Organized and led regular code review sessions and technical workshops to maintain high coding standards, fostering a culture of continuous learning and driving technical excellence within the engineering team. Projects

Real-Time Data Processing and Analytics Platform

• Created a data processing system with Hadoop for data storage, Spark for rapid analytics (boosting data processing speed by 40% over traditional methods), and Kafka for real-time data streaming, enhancing large-scale data management efficiency.

• Implemented Docker and Kubernetes, resulting in a 30% improvement in scalable deployment times across AWS infrastructure.

• Integrated Cassandra for data management and employed ETL techniques, which together improved data retrieval speeds and by 25%. Prediction of Diabetes in Pregnant Women

• Designed a machine learning tool using back propagation with gradient descent and sigmoid function as an activating function to train artificial neural networks to obtain a higher system accuracy and prediction of diabetes.

• Completed the proposed model with an accuracy of 91.4% as compared to some current models with a prediction accuracy of 88.7%. Data Visualizations on Violent Crime Rate in California

• Processed and analyzed a large dataset from the California Department of Public Health, detailing violent crime rates across various counties from 2000 to 2013, using Python for data cleaning and aggregation, ensuring accurate and comprehensive data visualization.

• Implemented a comprehensive data visualization platform using Streamlit and libraries like Plotly and Pandas to analyze and display violent crime trends in California from 2000-2013, resulting in enhanced public awareness and informed decision-making.

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