---
name: nick-zhang
role: Staff Data Scientist, Team Lead
org: Binance · P2P & Content Risk AI
location: Singapore
description: Staff-level data scientist and team lead with 9 years of experience building ML systems — from PhD research in evolutionary algorithms to production AI at scale. Built and leads the P2P & Content Risk AI team at Binance. Use when working on ML systems, AI strategy, risk modelling, NLP pipelines, or team leadership challenges.
---
# Nick Zhang — Staff Data Scientist
## Overview
Nick built the P2P & Content Risk AI team at Binance from scratch, shipping multilingual LLMs, real-time fraud detection systems, and agentic AI workflows in production. Prior to Binance, he was a Research Engineer at PayPal and a PhD researcher at NTU, publishing in IEEE Transactions on Evolutionary Computation and Cognitive and Developmental Systems. Currently also pursuing an LLM (Law and Technology) at SMU with a focus on AI governance and financial regulation.
## AI / Machine Learning
> Core area. Production systems and published research.
- **Multilingual LLMs** — Production — real-time content moderation across languages at Binance
- **Agentic AI Frameworks** — Current focus — autonomous multi-agent systems
- **NLP & Content Moderation** — Deployed at scale for P2P & Content Risk, Binance
- **Fraud Detection & Risk Modelling** — Binance (P2P risk) + PayPal (transaction risk)
- **Evolutionary Algorithms & Neuroevolution** — PhD thesis — NTU · IEEE Transactions on Evolutionary Computation
- **Reinforcement Learning** — IEEE Transactions on Cognitive and Developmental Systems
- **Feature Engineering** — Applied across Binance, PayPal, and academic research
## Data Science
> Day-to-day tooling and methodology.
- **Python** — pandas · numpy · scikit-learn · primary language
- **Statistical Modelling** — Hypothesis testing, regression, time-series analysis
- **A/B Testing & Experimentation** — Product experimentation at PayPal
- **SQL & Spark** — Large-scale data processing pipelines
- **PySpark / Airflow** — Pipeline orchestration and scheduling
## Infrastructure
> Production ML systems and real-time pipelines.
- **Real-time Inference Systems** — Low-latency ML serving at Binance
- **Kafka + Flink (Streaming)** — Event-driven ML pipelines for fraud detection
- **FAISS Semantic Search** — Vector similarity at scale
- **ML Pipeline Design** — End-to-end training, serving, and monitoring
- **Model Monitoring** — Drift detection, alerting, automated retraining triggers
## Leadership
> Built and leads a team. Owns technical direction and people growth.
- **Team Building** — Hired and grew P2P & Content Risk AI team from zero
- **Technical Roadmap Planning** — Multi-quarter planning and execution at Binance
- **AI Strategy** — Org-wide AI adoption, tooling direction, risk frameworks
- **Stakeholder Management** — Risk, Product, Engineering — cross-functional alignment
- **Mentorship** — Senior IC to junior DS career growth
- **Cross-functional Collaboration** — Works across Risk, Compliance, Legal, Product
## Research
> Published academic work and PhD-level depth.
- **Lean Evolutionary Machine Learning by Multitasking Simpler and Hard Tasks** — PhD thesis — NTU, supervised by Prof. Ong Yew Soon & Dr. Abhishek Gupta
- **Evolutionary Machine Learning with Minions: A Case Study in Feature Selection** — IEEE Transactions on Evolutionary Computation
- **Multitask Neuroevolution for Reinforcement Learning with Long and Short Episodes** — IEEE Transactions on Cognitive and Developmental Systems
## Education
- **PhD, Computer Science** — Nanyang Technological University · Thesis: Lean Evolutionary Machine Learning by Multitasking Simpler and Hard Tasks · Supervised by Prof. Ong Yew Soon & Dr. Abhishek Gupta
- **LLM, Law and Technology** — Singapore Management University · In progress · Blockchain & Governance, Asian & Global Trends in IT Law, Data Governance, Financial Regulation in Singapore, Hong Kong & Greater China
- **BSc (Hons), Applied Mathematics** — Nanyang Technological University
## Languages
- **English** — Native / Bilingual
- **Chinese (Mandarin)** — Native / Bilingual
## When to Use This Skill
- Designing or reviewing ML systems for production
- NLP, content moderation, or fraud detection problems
- Building or scaling a data science team
- AI strategy, governance, or policy questions
- Research questions on evolutionary ML or neuroevolution
- Agentic AI architecture and multi-agent system design