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AI Engineer with less than a year in Data Science & Machine Learning with hands-on AI/ML development
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Assessing your cultural and operational fit
Computer Science undergraduate at Sukkur IBA University, specializing in Data Science and Machine Learning, with hands-on experience in Python-based AI/ML development. Proficient in building and experimenting with machine learning models, data pipelines, and applying libraries such as NumPy, Pandas, and Scikit-learn. Backed by a strong algorithmic foundation in Java (DSA). Passionate about developing intelligent, data-driven applications, I thrive in collaborative, fast-paced environments and am eager to contribute to real-world AI engineering challenges as part of a forward-thinking team.
Sukkur IBA University
Bachelor's · Computer Science
August 1, 2023 – June 30, 2027
Superior College of Science, Hyderabad
Intermediate
June 1, 2019 – May 31, 2021
Mental Health Treatment Prediction
February 1, 2026 – March 31, 2026
Built an ML pipeline to predict mental health treatment needs, comparing multiple algorithms to achieve an 82% accuracy with a Random Forest model. Deployed the optimized model via FastAPI, creating a responsive backend capable of serving real-time predictions for healthcare applications. Developed a user-friendly frontend using React, integrating it with the FastAPI backend to enable seamless real-time interaction and prediction visualization.
MiniGit (Version Control System)
October 1, 2025 – November 30, 2025
Built a Java CLI version control tool supporting staging, custom commits, and isolated branching. Leveraged Java NIO for robust local storage, UUID-based object snapshotting, and timestamped logging. Implemented byte-level file comparisons to dynamically detect untracked, modified, and unchanged states.
Music Player using Circular Doubly Linked List (DSA Project)
November 1, 2024 – December 31, 2024
Designed and implemented a music player application using a Circular Doubly Linked List to enable efficient bidirectional navigation and continuous loop playback functionality. Built the frontend using HTML, CSS, and JavaScript, providing an interactive and user-friendly interface.
Cultural Fit Analysis
The candidate is an undergraduate with academic projects. The 'Mental Health Treatment Prediction' project shows an interest in applying AI to real-world problems, which could align with a forward-thinking team. The diversity of projects (ML, VCS, DSA/Web) indicates a broad technical curiosity. However, as an undergraduate with no professional experience, the cultural fit is largely speculative based on project choices and stated interests. The target role is AI Engineer, and the primary project aligns well, but the overall breadth of experience is limited to academic settings.
Soft Skills & Operational Fit
The candidate's profile mentions 'Analytical Problem Solving' and 'Agile Team Collaboration' as relevant coursework, suggesting an awareness of important soft skills. Project descriptions indicate an ability to work on multi-component systems (backend, frontend, ML model). However, without direct work experience or interview data, it's difficult to fully assess operational fit and actual soft skill proficiency.