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AI Engineer with 1+ years in Networking & Data Science
Ambitious AI and Data Science undergraduate with a strong foundation in predictive modeling and statistical analysis. Proficient in Python, R and MySQL, with hands-on experience building machine learning models to solve business problems. Passionate about applying data-driven techniques to deliver actionable insights and optimize decision-making. Seeking internship opportunities in Data Science, Model Engineering or AI-related roles.
Robert Gordon University
BSc (Hons) · Artificial Intelligence and Data Science
August 1, 2025 – Present
Informatics Institute of Technology
Foundation Certificate · Higher Education
August 1, 2024 – June 30, 2024
College of Technology
NVQ Level(4) · Telecommunications Technology
August 1, 2022 – June 30, 2023
G/Dikkumbura Sri Siddhartha National School
GCE Advanced Levels
June 1, 2012 – May 31, 2021
Sri Lanka Telecom
Network Engineer (Internship)
January 1, 2023 – December 31, 2023
Matara, Southern Province, Sri Lanka
Sierra Construction Limited
Fiber Technician (Internship)
January 1, 2022 – December 31, 2023
Kelaniya, Western Province, Sri Lanka
Multimodal Gold & Silver Price Prediction & Market Trend Analysis
January 1, 2025 – June 1, 2026
Developed a predictive analytics application using Python, Flask, TensorFlow and joblib-based models to generate gold and silver forecasts, market trend insights and economic interpretation from historical and macroeconomic data.
View ProjectTelco Customer Churn Prediction
January 1, 2025 – June 1, 2026
Built machine learning models (Decision Tree and Neural Network) to predict customer churn using telecom customer data.
View ProjectReturn & Refund Abuse Detection Pipeline
January 1, 2025 – June 1, 2026
Developed an end-to-end AWS-based data pipeline to detect fraudulent return behaviour using data cleaning, feature engineering and an abuse scoring model (AWS Glue, S3, Redshift, Step Functions).
View ProjectReturn & Refund Abuse Detection
January 1, 2025 – June 1, 2026
Built a hybrid ML + LLM web application that detects fraudulent e-commerce return behaviour using a Random Forest classifier with engineered abuse signals, served via a FastAPI backend with local LLAMA 3.2 reasoning and a vanilla JS frontend.
View ProjectCultural Fit Analysis
The candidate's academic projects show a strong interest in applying AI/ML to diverse business problems (finance, e-commerce, telecom), which aligns well with a problem-solving oriented culture. The inclusion of both ML model development and data pipeline projects indicates a breadth of interest in the AI/ML lifecycle. The internship experiences, while not directly AI-related, demonstrate a willingness to learn and contribute in technical environments. The candidate is currently pursuing a degree, suggesting a growth mindset.
Soft Skills & Operational Fit
The candidate highlights analytical & critical thinking, problem-solving, adaptability, and team collaboration as soft skills. These are valuable for an AI Engineer role, especially in problem identification, model design, and collaborative development. The academic projects demonstrate an ability to apply these skills to real-world scenarios, albeit in a controlled environment.