WP. Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia
I am a Data Science Graduate from Tunku Abdul Rahman University of Management and Technology (TAR UMT). I am currently working as a Credit Risk Modeler in the Finance Industry, using Python, SQL and SAS. In addition, I have 6 months internship experience in Generative AI and ML. I possess hands-on experience with Large Language Models (LLMs), having applied them in NLP as well as Audio and Vision models. I also have a firm foundation in classical Machine Learning and Deep Learning. I am passionate about uncovering hidden knowledge and patterns in data and applying these insights to solve business/organisational problems. My areas of interest include Generative AI, Large Language Models (LLM), Agentic Workflow, Diffusion Models, Machine Learning, Deep Learning, MLOps/LLMOps and Data Engineering. I have hands-on experience in Data Engineering, particularly with technologies such as Hadoop, HDFS, Spark Structured Streaming, Apache Kafka, Hive and HBase. This was complemented by a course in Distributed Systems and Parallel Computing, where I gained practical experience with CUDA in C++, OpenMP, and MPI. I also have a firm foundation in Data Warehousing and ETL. Additionally, I have acquired fundamental knowledge and hands-on experience in Cloud Computing (Azure, AWS, GCP), Blockchain Application Development (Solidity, Ethereum, Chainlink, and Web3) and the Principles of Marketing. I am also mindful of IT Security best practices and possess a foundational understanding of Software Engineering concepts. Beyond academic pursuits, I am committed to ongoing self-improvement as I believe that personal growth augments not only my skills but also my ability to contribute meaningfully to collaborative endeavours.
- Assisted in the development and validation of new Credit Risk Scorecards for a SME portfolio, gaining exposure to the use of customer behavioural and financial data in credit risk assessment. - Migrated SAS data pipelines to Python while ensuring business rule consistency. - Served as a key developer in coding a Credit Risk Scoring Engine for a SME portfolio for both batch and live scoring, which are fully coded in Python. - Produced Model Monitoring Reports on the performance of scorecards for Large Corporate borrowers. - Assisted in preparing datasets for analysis for my department and other Business Units.
- Developed and deployed AI models (NLP, Audio, Vision) on Cloud platform, including Agentic development and LLM fine-tuning. Employed PyTorch, Vector Database and RAG (Retrieval Augmented Generation) in the development process. - Gathered, cleaned, and analysed data to align with project objectives. - Worked with cross-functional teams and business partners to understand business requirements and provide analytical insights. - Assisted in testing and validating AI algorithms and LLM solutions. - Maintained thorough documentation of research and development processes.