Experience

Goldman Sachs — Quantitative Strategist (Associate)

May 2022 — Jan 2026

Led an end-to-end OTC client FIX flow for equity-linked products (FIX protocol → Java microservice processor → GS Slang-connected pricing), driving a 150% increase in trades from the client.
Built pricing data ingestion for structured products: stored product datasets in MongoDB via scheduled jobs and persisted curated datasets to AWS S3 for redundancy and downstream consumption.
Orchestrated feature engineering workflows using Apache Airflow on EC2, running Python transformations for normalization and dimensionality reduction, improving ML prediction stability by ~50%.
Developed analytics pipelines and Superset dashboards to monitor turnaround time and error distributions across distribution channels; metrics used to forecast customer flow and support deal execution.
Helped maintain Kafka streaming for microservices with IAM-based access control and archival to S3.

NUS — MSc Statistics (May 2024 — Present): applied statistical learning, NLP, time series, finance methods.
NUS — BComp Computer Science (AI specialisation) (2018 — 2022): ML foundations, big data systems, CV, ethics.

Earnings call “Reverse RAG” — traced AI-generated questions back to source transcript sentences using LangChain chunking, SentenceTransformers embeddings, and a FAISS index.
Real estate niche CRM — Dockerized React + Express + Postgres stack with API-based channel integrations (WhatsApp/Instagram/Facebook) and workflow automation via n8n; experimented with self-hosted Llama3-8B for lead query replies.
Crypto low-cap trading bot — tracked KOL posts, scored sentiment with FinBERT, and used XGBoost features (market cap, volume, volatility) to inform holding time.

H2O Generative AI Track