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Red Dot Payment / Data Scientist
Data Scientist currently working in the FinTech industry. Aspires to become one of the best Machine Learning engineer on Earth. Passionate about all things on AI/ML. Most proficient in machine learning/ deep learning in Computer Vision and Natural Language Processing. Experienced in creating web games, websites, web applications, software applications, IOS and Android applications. Strong in both
I aspire to become one of the best Machine Learning Engineer on Earth.
Fraud Detection(Natural Language Processing) I am currently in-charged of building Machine Learning/ Deep Learning pipelines for the prediction of suspicious invoices by the merchants of Red Dot Payment, to map their Merchant Category Code(MCC) to the items sold in the invoices.
Using the tools from Amazon Web Services(AWS), I was part of a team of 5 data engineers. We build ETL(extract, transform and load) pipelines on AWS using pyspark and python. Tech used: python, pandas, numpy, pyspark, unittest, AWS S3, AWS Glue, AWS Athena, AWS Lambda, AWS Sagemaker, AWS RDS, AWS DynamoDB.
2017 - 2018, withdrawn after first sememster
Completed 4 projects during the Web Development Immersive course by General Assembly
Using Java, .Net and C#, I am currently working in a team of experienced professionals. We create software products for UOB and I am the primary developer to create functioning applications for our clients, with the occasional guidance from my seniors.
• Completed 12-week full-time intensive programme on full-stack web development • Developed 4 full-stack and front-end applications ► Survive! • A simple survival game that requires the player to use arrow keys to dodge attacking monsters and collect power-ups to survi
A level results: BCC/A
O level L1R5 : 15
Nanyang Technological University(withdrawn) / Humanities
A locally hosted website that tests users for their personality and recommends books based on their personality types. Built using HTML, CSS, Javascript, Node, Express, Bootstrap, PostgreSql.
