About Me

Hi, I'm Aditya, a tech enthusiast with a strong interest in web development, currently building my skills in Python and AI/ML. I enjoy creating responsive, maintainable web applications that are efficient and user-friendly.

At Tata Technologies, I work as a Graduate Engineer Trainee, contributing to automation testing on 3DEXPERIENCE ENOVIA using Eggplant Functional, supporting enterprise-level systems and internal workflows.

Alongside this, I’m actively strengthening my skills in Data Analytics and the MERN stack, while embracing best practices in modern web development and test automation. Passionate about clean code, scalable architecture, and continuous learning, I aim to grow into a versatile and impactful engineer.

Age: 22

Place: Bengaluru, Karnataka

Phone: 8072050055

Email: adityajai243@gmail.com

My Thoughts

I’m not particularly eager to define myself by my work. I define myself by the work I want to do. Skills can be taught, but personality is inherent. I prefer to keep learning, continue challenging myself, and do interesting things that matter. I'm Always curious, humble, and courageous.

My Goal

My abundant energy and boundless enthusiasm fuels me in the pursuit of many interests, hobbies, areas of study. I’m a fast learner, able to pick up new skills and juggle different projects and roles with relative ease. I like to work on the public issues which can be solved using technology.

What I’m good at?

Technical Skills

Python, React.js, MongoDB, MySQL, DSA, Machine Learning, SenseTalk, Eggplant Functional, Git, Agile.

Familiar With

ENOVIA, JIRA

Soft Skills

I prioritize efficient time management, collaboration, curiosity, adaptability, and strategic thinking. These qualities ensure effective problem-solving and sustained success in all endeavors.


Tools known

VS Code, Jupyter Notebook, MongoDB Atlas, Github, Postman, Eggplant DAI, 3DEXPERIENCE.


Things I Love

Learning new things, Travelling, Solving sudoku, Spending time outdoors, Cooking and Trying out new Food

My Works

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QuickChat

Developed QuickChat, a real-time chat application using React.js and Firebase. Implemented user authentication, message synchronization, and database management with Firebase Firestore. Ensured a responsive design for seamless user experience across devices, showcasing expertise in modern web development and real-time data handling.
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Driver Drowsiness Detection

This project utilizes deep learning and Haar cascade files for driver drowsiness detection. Analyzing real-time facial expressions and eye movements, it alerts drivers to signs of drowsiness, enhancing road safety by issuing timely warnings and reducing the risk of accidents caused by fatigue.
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Stock market forecasting

Implemented a time series forecasting model for stock prices using a stacked Long Short-Term Memory (LSTM) network. The project involved data collection, preprocessing, and feature engineering, followed by the design and training of the LSTM model. Achieved accurate predictions of stock market trends, showcasing the model's capability to capture temporal dependencies.
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Youtube Video Downloader

Developed an android application that helps to download youtube videos from youtube by just providing the URL of the video/shorts, used pytube, python kivy to create the application and used bulidozer to convert it to an apk.
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Soil Type Classification

Developed a deep learning model for soil type classification using the AlexNet architecture. The project involved data preprocessing, model training, and evaluation on a dataset of soil images.
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Diabetes Prediction

Developed a machine learning model to predict diabetes based on patient data. The project involved data preprocessing, feature selection, and model training using algorithms like Logistic Regression and Random Forest. Achieved high accuracy and provided insights into key risk factors. Used Flask for implementation.
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Sepsis Disease Prediction

Developed a machine learning model to predict sepsis disease based on patient data. The project involved data preprocessing, feature selection, and model training using algorithm Random Forest.
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Customer Segmentation

Conducted a customer segmentation project using R, employing K-means clustering to group customers based on characteristics like gender, age, annual income, and spending patterns. The project involved data preprocessing, cluster analysis, and visualization to identify distinct customer segments.

My Experience

Graduate Engineer Trainee

Tata Technologies

Bengaluru, Karnataka

January 2025 – Present

Part of the Automation Testing team, focusing on 3DEXPERIENCE ENOVIA using Eggplant Functional and DAI. Responsible for scripting automated test cases, validating system workflows, and ensuring software quality.

Data Science Virtual Intern

LetsGrowMore

Remote

April 2023 – May 2023

Completed a virtual internship focused on data science, involving hands-on projects in data analysis, machine learning, and data visualization. Gained practical experience in Python, Pandas, and data manipulation techniques.

Software Developer Virtual Experience

JP Morgan Chase &Co.

Remote

January, 2023

Google Cloud Facilitator

CloudReady Program

April 2022 – July 2022

Remote

Contact Me