About

Shalini Choudhary is a highly motivated and skilled software engineer with a strong background in problem-solving and data structures and algorithms. She graduated from SRM University in 2020 with a Bachelor of Technology in Information Technology. Shalini has hands-on experience in A/B testing and is a quick learner with a growth mindset. Shalini is experienced in building frontend applications using ReactJS, following the best coding practices along with proper code formatting and linting. She has devised responsive and accessible web pages using HTML5, CSS3, and JavaScript. She has sound knowledge of MongoDB, NodeJS, and other backend technologies and has experience working within an agile environment. Shalini has a strong technical skill set, including Python, C++, JavaScript, HTML5, CSS3, ES6, Bootstrap, Web Accessibility, React, TensorFlow, Keras, VS Code, Sublime Text, NVDA, Git, GitHub, Gitlab, Bitbucket, JIRA, Confluence, Matplotlib, Seaborn, Netlify, and Heroku. Coding excites Shalini, and she has a strong online presence on platforms such as LeetCode, HackerRank, GeeksforGeeks, and GitHub. She is currently working as an Associate Experience Technology L1 at Publicis Sapient, where she has designed new variations for the microapp, resulting in increased acknowledgement rates from 54% to 85% amid A/B testing. She has also collaborated with the team to create reusable components and authored unit test cases, resulting in enhanced coverage by 30%. Additionally, she has developed scripts for Tealium tags, which helped to improve the page loading time and enhanced the performance rate of the website by 10%. Shalini has previously worked as a Junior Associate Technology at Publicis Sapient, where she initiated ES6 along with code linters and formatters resulting in improved code quality. She has also worked as a Data Science Intern at Takenmind, where she focused on predicting the number of employees who would leave the company based on low satisfaction levels, low promotional rates, low salary, and longer working hours. She used Gradient Boosting Algorithm for performing the prediction, which resulted in an accuracy of 80%. Shalini's relevant experience in the software engineering field is 2.36 years, and her technical expertise covers a wide range of areas, including frontend and backend development, data science, and problem-solving.