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Data Science with 1+ years in AI, NLP, and Machine Learning
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Assessing your cultural and operational fit
Data Science and AI undergraduate with hands-on experience building and deploying end-to-end machine learning pipelines, NLP systems, LLM-powered applications, and computer vision models. Proficient in Python, PyTorch, TensorFlow, and LangChain. Experienced in RAG architectures, transfer learning, and full-stack ML deployment using Streamlit and Flask. GPA: 3.84/4.0.
Pakistan Institute of Engineering & Applied Sciences (PIEAS)
Bachelor of Computer and Information Sciences · Computer and Information Sciences
September 1, 2023 – June 1, 2027
Buildables Fellowship
Data Science Fellow
August 1, 2025 – November 1, 2025
India
Excelerate
Data Visualization Associate Intern
August 1, 2025 – Present
India
AI Job Application Assistant (Multi-Agent System)
June 15, 2026 – June 19, 2026
Built a multi-agent LLM system with 4 specialized agents collaborating in a pipeline for job analysis, resume tailoring, cover letter writing, and interview prep • Integrated LLaMA 3.3 70B via Groq API with LangChain for agent orchestration
View ProjectLive Lecture Note-Taker — Real-Time AI Speech-to-Text System
June 14, 2026 – June 23, 2026
Built a real-time system using Groq Whisper and LLaMA 3.3 70B that transcribes live audio and generates structured notes with a dynamic knowledge graph • Designed an incremental 5-second chunk processing pipeline with live-updating Streamlit UI
View ProjectRAG Chatbot - Chat with PDF using AI
January 1, 2025 – December 31, 2025
Built a Retrieval Augmented Generation (RAG) chatbot enabling users to upload PDFs and query them in natural language. Implemented document chunking, HuggingFace sentence embeddings (all-MiniLM-L6-v2), and ChromaDB vector database for semantic search. Integrated LLaMA 3.3 70B via Groq API for fast inference with source page citation; deployed live on Streamlit Cloud.
Brain Tumor Detection from MRI Scans
January 1, 2025 – December 31, 2025
Developed a computer vision deep learning model to classify brain MRI scans into 4 categories: Glioma, Meningioma, Pituitary, No Tumor. Applied transfer learning with ResNet18 pretrained on ImageNet, fine-tuned on 5,600 MRI images achieving 87% test accuracy. Deployed as an interactive Streamlit web app with confidence scores and probability breakdown per class.
YouTube Video Summarizer
January 1, 2025 – December 31, 2025
Built an NLP-powered web app that fetches YouTube transcripts and generates AI summaries in 3 formats: concise, detailed, and bullet points. Integrated Groq API with LLaMA 3.3 70B for fast inference; deployed on Streamlit Cloud with download functionality.
Food Delivery Delay Prediction System
January 1, 2025 – December 31, 2025
Built a predictive ML model on rider, order, and traffic features achieving 92% prediction accuracy. Developed a Flask web app for real-time delay predictions enabling proactive customer alerts.
NASA MeteorSense AI
January 1, 2025 – December 31, 2025
Built an AI-based Near-Earth Object hazard prediction system using XGBoost on NASA NEO API data. Achieved 96.11% classification accuracy with an end-to-end pipeline covering feature engineering, model optimization, and real-time Streamlit dashboard.
Fake Job Post Detection
January 1, 2025 – December 31, 2025
Developed an NLP classifier using TF-IDF vectorization with Logistic Regression and XGBoost achieving 98% accuracy. Deployed a Streamlit interface for real-time fraudulent job listing detection on the Kaggle dataset.
Python Data Fundamentals
DataCamp
June 11, 2026 – Present
SQL Fundamentals
DataCamp
June 11, 2026 – Present
Excel Fundamentals
DataCamp
June 11, 2026 – Present
Intro to Power BI and DAX
DataCamp
June 11, 2026 – Present
Achieved a perfect score (100%) on the Data Scientist — Artificial Intelligence exam, indicating exceptional proficiency in the subject matter.
Strengths
Limitations
Cultural Fit Analysis
The candidate's academic projects demonstrate a strong interest and initiative in cutting-edge AI/ML domains, aligning well with an AI Intern role. The diversity of projects (computer vision, NLP, RAG, multi-agent systems, predictive analytics) shows a broad curiosity and willingness to explore different areas within AI. Participation in GDGOC and AWS Cloud Club indicates engagement with technical communities and a proactive learning attitude. However, the psychometric test score of 199/500 is a significant concern regarding cultural fit, as it suggests potential issues with work attitude, stress handling, or team collaboration, which are critical for any role.
Soft Skills & Operational Fit
The candidate's project descriptions highlight an ability to work in teams (Buildables Fellowship) and present project outcomes, suggesting good collaboration and communication skills. The focus on deploying real-time applications and end-to-end pipelines indicates a practical, results-oriented approach. The psychometric test score is low, which might indicate potential challenges in logical reasoning, work attitude, stress handling, or team collaboration, requiring further investigation.
Scored 85% on the Python Internship Test, demonstrating strong Python programming skills, but with some room for improvement in specific areas.
Strengths
Limitations
Achieved a perfect score (100%) on the Power BI exam, indicating excellent proficiency in Microsoft Analytics and Power BI.
Strengths
Limitations