MSc Data Science & Artificial Intelligence candidate at the University of Liverpool with hands-on experience in machine learning, NLP, predictive modeling, and data visualization. Presented research at a national conference. Skilled in Python, SQL, TensorFlow, and Power BI, with a track record of designing end-to-end AI solutions that deliver measurable business impact. Actively seeking challenging opportunities in Data Science and Machine Learning.
Developed a classification model (Random Forest, XGBoost) enabling proactive retention strategies for a telecom customer base.
86% accuracyBuilt an image classification model using CNNs in TensorFlow, improving early diagnosis and reducing crop losses.
~90% accuracyApplied NLP and supervised learning to classify 50,000+ tweets for brand monitoring pipelines.
82% F1-scoreDesigned a sensor-based system integrated with ML algorithms to predict pollution levels in real time. Presented at a national conference.
~90% accuracyDeveloped clustering and predictive models (K-Means, Hierarchical) to identify high-value customer segments, boosting targeted marketing effectiveness and retention by 15–20%.
~85% accuracyOpen to internships, research collaborations, entry-level roles, or a chat about AI and machine learning. Drop a line on email or LinkedIn — whichever you prefer.