Hello, I'm
Ryan Chin
Hello, I'm
A snapshot of who I am and what drives me.
I'm a Year 3 Bachelor of Computer Science (Data Science) student at Universiti Malaya, experienced in end-to-end data lifecycles. From engineering robust data pipelines to deploying advanced predictive models and generative AI systems, I am passionate about transforming complex, unstructured data into actionable business intelligence. My focus is on delivering scalable, data-driven solutions that solve real-world problems, such as through award-winning interactive dashboards or LLM-based multi-agent platforms for financial analysis.
BCS (Data Science) — Universiti Malaya
English · Malay · Mandarin
ML · Data Engineering · LLM Agents · Analytics
Where I've contributed and grown.
Universiti Malaya — Faculty of Computer Science & IT
Assist lecturers in conducting tutorials and lab sessions. Support students in programming fundamentals, data structures, and introductory data science courses.
Universiti Malaya — Faculty of Computer Science & IT
Guided peers through hands-on exercises in database management and statistics for data science. Helped troubleshoot code and clarify concepts during lab hours.
Things I've built and experimented with.
An intelligent stock analysis and portfolio management system for the Bursa Malaysia market. Employs a Multi-Agent System (MAS) and LLMs to synthesize fragmented data and provide transparent investment recommendations.
An NLP project that normalizes noisy, informal Malaysian tweets (containing slang, abbreviations, and misspellings) into standard, formal text in both English and Malay.
Encompasses dataset simulation, feature engineering, predictive modelling, and model interpretation in the financial domain using traditional ML alongside GenAI and Small Language Models (SLMs).
Analyzes historical weather data and forecasts rainfall patterns for Kuala Lumpur. Includes data retrieval, cleaning, EDA, feature engineering, and the evaluation of five ML regression models.
A machine learning project predicting company bankruptcy. Developed and evaluated models (XGBoost, Ridge Regression, Random Forest) with data cleaning, feature engineering, and hyperparameter tuning to address imbalanced classes.
An analysis of public transport figures in Klang Valley for prescriptive recommendations, featuring deep EDA, data modelling, and interactive dashboarding.
A data visualization project that merges multiple datasets to investigate crime statistics and their relationships with other socioeconomic factors.
Compares the performance of Apache Hadoop (MapReduce) and Apache Spark by implementing and benchmarking three queries on the same dataset to evaluate how these frameworks handle identical workloads.
A web-based management platform for roster management, city-to-city travel optimization, and player tracking. Heavily utilizes data structures and algorithms such as graphs, Depth-First Search (DFS), stacks, and queues.
A desktop nature conservation awareness application featuring user accounts, a quiz system, daily logins, a point shop, and live news retrieval via API.
Technologies and tools I work with.
Recognitions I'm proud of.
Competed in a national-level data science competition, tackling real-world analytics problems with creative data-driven solutions, including a best interactive dashboard built with PowerBI
Demonstrated strong analytical and presentation skills in a multi-round data challenge event.
Industry credentials I've earned.
Core cloud computing concepts, AWS global infrastructure, pricing, security, and key services.
Data analytics fundamentals using Google Cloud tools — BigQuery, Looker, and data pipeline best practices.
Advanced analytics techniques, including statistical analysis, machine learning, and data visualization.
Feel free to reach out — I'd love to connect!