Ashutosh Yadav
A Master’s student at University College Dublin, with hands-on experience in Java, Spring Framework, Angular Framework, MongoDB, MySQL, REST APIs, and web technologies like HTML, CSS, JavaScript, and TypeScript. I have worked on developing robust and scalable applications, designing RESTful APIs, and integrating modern frameworks to enhance user experiences. Driven by a passion for technology, I am eager to continue learning and refining my skills to deliver innovative solutions that address real-world challenges effectively.
Work Experience
A brief overview of my professional journey, showcasing key roles and contributions.
Capemini Technologies - Software Engineer Analyst
March 2024 - Present
Engineered and deployed settlement and billing workflows for a SaaS theatrical booking platform used by Sony & Universal Studios, ensuring accurate revenue distribution across 1000+ transactions weekly.
Reduced manual settlement approval time by 40% through automated workflow design, improving operational efficiency.
Delivered 4 production-grade application screens as part of Agile Scrum teams with bi-weekly releases, collaborating with QA, Product Owners, and Business Analysts to align deliverables with client needs and enable seamless version upgrades.
Led a training batch of new hires in Core Java, providing mentorship and technical guidance alongside project deliverables; collaborated with team leads to accelerate onboarding, foster teamwork, and ensure fresher readiness for live projects.
Orchestrated management of private equity data in the Data Ops team, evaluating fund types (VC or PE) and directing information based on tracking criteria, improving workflow efficiency by 30%.
Collaborated within a team to optimize ticket management processes, resulting in significant cost reduction.
Implemented efficient data collection and analysis methods, ensuring accurate and timely insights.
Conducted comprehensive market research and data analysis, contributing to a 15% increase in overall client retention and satisfaction rates.
Morningstar, Inc - MDP Associate
October 2023 - February 2024
TCS iON - Intern
July 2022 - August 2022
Automated sentiment detection from textual comments and feedback using machine learning techniques.
Achieved a prediction model with 85% accuracy in categorizing comments as Positive, Negative, or Neutral.
Employed the Word2Vec algorithm and optimized data preprocessing to improve prediction outcomes.
Collaborated within a team to streamline data collection and analysis processes.
Developed and optimized machine learning models using Python and TensorFlow, achieving an 85% accuracy rate.
Web Developer - Intern
April 2022 - July 2022
Helped design websites for clients, focusing on both front-end and back-end development.
Utilized AngularJS for the front end to create dynamic and interactive user interfaces.
Used Python for backend development, ensuring robust and scalable server-side logic.
Contributed to web development projects, focusing on enhancing user experience and interface.
Educational Background
A brief overview of my educational journey
Thakur College of Engineering And Technology
Bachelor's of Engineering - Information Technology
University College Dublin
Master's of Science - Computer Science
September 2025 - August 2026
July 2019 - june 2023
Personal Projects
Explore my personal coding projects showcasing my skills.
Engineered a Flight Booking System using Core Java, Spring Boot, RabbitMQ and Microservices architecture. Developed the front end with Angular and integrated a secure payment gateway using Razorpay. Utilized Swagger API and Postman for API documentation and testing.
Developed a modular Training Management System utilizing Java and Spring Boot, Google Gemini LLM. Designed the front end using Angular and implemented a microservices architecture with Spring Boot. Integrated MongoDB and MySQL for efficient data management.
Developed a web-based disease prediction system that analyzes entered symptoms to predict potential diseases. Utilized TensorFlow and the Random Forest algorithm to train the ML model, achieving an 85% prediction accuracy.
SoundSphere - Free Spotify Playlist Downloader
A full-stack application built with Node.js, Express.js, MongoDB, and React, designed for personal use to download my Spotify playlists for free. It utilizes Axios to make API requests for fetching playlist data and yt-dlp-wrap to search and download high-quality audio files, storing them in my MondoDB Atlas database for easy access.