Ke Xin Chong

Senior Data Scientist (Fraud & Risk) | Machine Learning Engineer | MSCS @ Georgia Tech | Web3

As a Senior Data Scientist with 6+ years of experience, I build and deploy machine learning solutions that solve critical challenges in the payment and risk management industry. From rapid prototyping to end-to-end productionization, I am committed to enhancing fraud detection and creating data-driven, resilient financial systems.

A few highlights from my work include:

✔️ Reduced Real-Time Fraud Latency: Redesigned a fraud detection system using Apache Kafka, cutting average transaction processing time from 850ms to 450ms at Advance.AI.

✔️ Enhanced Compliance with NLP: Designed and deployed text classification models that detected non-compliant e-commerce listings, reducing manual review workload by 40%.

✔️ Improved ML Model Performance: Built a neural network to complement a rule-based engine, boosting fraud detection recall by 12% during atypical transaction spikes.

While my core experience is in FinTech risk, I am passionate about applying these principles to enhance security and trust in decentralized systems. As a member of the Blockchain Club @ GT and a Solidity developer, I am exploring the intersection of AI and blockchain. This includes co-developing "Voicy," a decentralized AI voice marketplace on the Flow blockchain that automates royalty payments to creators via smart contracts.

I am currently seeking Senior Data Scientist or Machine Learning Engineer roles in either FinTech (Risk) or Web3. Let’s connect to explore how we can collaborate to drive data-driven innovation.As a Senior Data Scientist with 6+ years of experience, I build and deploy machine learning solutions that solve critical challenges in the payment and risk management industry. From rapid prototyping to end-to-end productionization, I am committed to enhancing fraud detection and creating data-driven, resilient financial systems.

A few highlights from my work include: ✔️ Reduced Real-Time Fraud Latency: Redesigned a fraud detection system using Apache Kafka, cutting average transaction processing time from 850ms to 450ms at Advance.AI. ✔️ Enhanced Compliance with NLP: Designed and deployed text classification models that detected non-compliant e-commerce listings, reducing manual review workload by 40%. ✔️ Improved ML Model Performance: Built a neural network to complement a rule-based engine, boosting fraud detection recall by 12% during atypical transaction spikes. While my core experience is in FinTech risk, I am passionate about applying these principles to enhance security and trust in decentralized systems. As a member of the Blockchain Club @ GT and a Solidity developer, I am exploring the intersection of AI and blockchain. This includes co-developing "Voicy," a decentralized AI voice marketplace on the Flow blockchain that automates royalty payments to creators via smart contracts. I am currently seeking Senior Data Scientist or Machine Learning Engineer roles in either FinTech (Risk) or Web3. Let’s connect to explore how we can collaborate to drive data-driven innovation.

Georgia Institute of Technology

Master of Science - MS, Computer Science

Jan 2025 - Dec 2025

Specialisation in Machine Learning

Nanyang Technological University Singapore

Bachelor of Sciences(BS), Mathematical Sciences

B.Sc. (Hons) in Mathematical Sciences (Applied Math)

Minor in Computing and Data Analysis