AI Engineer with less than a year in Machine Learning and Data Science with hands-on project experie
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Computer Science student specializing in Machine Learning and Data Science with hands-on experience in building ML models using Python, Scikit-Learn, and Pandas. Skilled in data analysis, feature engineering, and model evaluation. Seeking an internship to apply and grow practical skills.
FAST-NUCES, Chiniot Faisalabad Campus
Bachelor of Science · Computer Science
August 1, 2023 – Present
MetaCog-Eval – LLM Metacognition Benchmark
March 1, 2026 – April 1, 2026
Designed a benchmark dataset to evaluate metacognitive capabilities in large language models (LLMs). Implemented evaluation tasks including confabulation detection, confidence calibration, and adversarial testing.
Customer Churn Prediction
November 1, 2025 – December 1, 2025
Built and evaluated machine learning models (Logistic Regression, Random Forest, XGBoost) for customer churn prediction on a real-world dataset. Improved model performance using feature engineering, hyperparameter tuning, and evaluation metrics such as accuracy and F1-score.
Student Marks Prediction
October 1, 2025 – November 1, 2025
Predicted marks for Sessional 1, Sessional 2, and Final exam marks using regression models on a student performance dataset. Performed data preprocessing, feature engineering, and cross-validated to improve prediction accuracy.
Weather Forecast Prediction
August 1, 2025 – September 1, 2025
Processed and analysed 30+ years of historical weather data using NASA API and identified seasonal patterns to support weather forecasting. Performed data preprocessing and time-series trend analysis and deployed via Streamlit.
Netflix Shows Analysis Dashboard
April 1, 2025 – May 1, 2025
Built an interactive Streamlit dashboard to analyse a Netflix dataset with filtering by genre, country, and rating. Deployed via Streamlit, demonstrated end-to-end data wrangling, analysis, and visualization.
AI Fluency: Foundations & Frameworks
Anthropic
January 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects are all academic and heavily focused on machine learning and data science, which aligns with an AI Engineer role. The participation in competitions (Google DeepMind × Kaggle, NASA Space Apps Challenge) shows initiative and a drive for practical application. However, the lack of professional experience or diverse team projects limits the assessment of cultural fit beyond technical alignment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on structured problems and deliver functional prototypes. The academic nature of all projects suggests a learning-oriented mindset. However, there is no information to assess stress handling, team collaboration, or communication clarity in a professional setting.