Bushra Shaikh

Aspiring data scientist currently pursuing an MSc in Computer Science with AI, aiming to contribute to innovative, data-driven projects at Boston Consulting Group (BCG). Strong foundation in data analysis, machine learning, and statistics. Skilled in Python, pandas, and modern development tools. Passionate about turning complex data into clear, actionable insights. Comfortable working on collaborative coding tasks and visualising results effectively. Eager to grow in a client-facing environment and apply core ML techniques to real-world business problems. Actively building project coordination and communication skills through academic and practical experience.

Full-Stack Developer, Profound Edutech Pvt Ltd (Dec 2022 - Jul 2023): Successfully completed a comprehensive Full-Stack Developer course, mastering essential programming languages and applying them effectively in the development of a final project, showcasing technical proficiency and problem-solving skills.

• Presentation: "The Impact on Open Source Projects Due to C++ Templates and Lambdas" at MIT-World Peace University, during the Hinweis Second International Conference on Advances in Software Engineering and Information Technology (ASIT) on January 1, 2023.
• Key Contributions: Research focused on the significant role of C++ templates and lambdas in enhancing customization and efficiency in programming languages, including C++, Java, and C#.
• Open Source Impact: Highlighted their transformative applications in open-source projects, enabling developers to implement more flexible and efficient code.
• Smart Fertilizer Recommendation System (MIT-World Peace University, January 1, 2023): This innovative project focuses on optimizing fertilizer usage by leveraging advanced algorithms to analyze soil quality, crop requirements, and environmental factors. The system aims to enhance agricultural productivity and sustainability by providing precise, data-driven fertilizer recommendations tailored to specific farming needs.

• Football Data Analysis: Using Excel, Python, Pandas, Matplotlib to clean, explore and analysis the data and understand what factors made the team win.
• Practical Data Analysis: Using Weka/Python I had to code and analyze the outcome of the model, changing the parameters and writing a report on the same.
• Emotion Recognition of Speech: Group project; I had to code a CNN Model using feature extraction methods to find the best training and testing accuracy and writing report for the same. Achieved 87% accuracy on emotion classification using CNNs with MFCC features.
• Fashion Mnist Deep Learning: Using dataset of fashion mnist I had coded a CNN model and made a video of the model demonstration.
• Prediction of Match Winning Team: Utilizing IPL match data, including parameters like team rankings and scoring scales, to develop an algorithm for predicting winning probabilities. Logistic Regression is employed to analyze patterns and forecast outcomes effectively. Optimized IPL win prediction with logistic regression — improved validation accuracy from 68% to 76% by feature selection.
• Optimization of Double Expansion Chamber Reactive Muffler for Maximum Transmission Loss: enhancing sound wave transmission loss by adding baffles and extending inlet/outlet structures using COMSOL Multiphysics