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Portrait of Ray Zhang

SHANGHAI · 2026

Quantitative Research × Backend & AI

RAY
ZHANG

Turning data into testable systems.

Mathematics and Computer Science undergraduate working across quantitative research, full-stack products and AI delivery—with solid engineering fundamentals and strong visual judgment.

数学与计算机科学本科生,关注量化研究、全栈产品与 AI 交付;工程基本功与视觉判断并重。 Explore↓
TOP 30%Paris Quant Challenge
1.55Out-of-sample Sharpe
48HProduct sprint

01 / PROFILE

A research toolkit
built for evidence.

My focus is the complete loop: reliable data, measurable hypotheses, clean engineering, chronological validation and clear risk communication.

关注从可靠数据、可度量假设、工程实现,到时序验证与风险表达的完整闭环。
01
⌁

Market Data

Returns, volatility, volume, momentum, rolling statistics and data-quality checks.

市场数据、滚动统计与数据质量检查
02
△

Research Design

Hypothesis definition, feature construction, chronological splits and rolling validation.

假设定义、特征构建与时序验证
03
∿

Risk Analytics

Sharpe ratio, drawdown, turnover, trading costs, exposure and interpretable reporting.

收益风险、交易成本与可解释报告
04
{ }

Quant Engineering

Python, Pandas, Polars, modular experiments, Git collaboration and AI-assisted analysis.

Python 数据流程、模块化实验与协作

02 / BACKEND & AI ENGINEERING

From data pipelines
to product services.

My backend practice grew from data-intensive research and product delivery: cleaning high-frequency datasets, building modular Python workflows and coordinating APIs under deadline.

后端实践来自数据密集型研究与产品交付:高频数据清洗、模块化 Python 流程,以及限时环境中的 API 联调。
01INGESTraw market / product data
→
02VALIDATEschema / missing / outlier
→
03PROCESSPython / modular logic
→
04SERVEAPI / interface / output
PRACTICEDB—01

Data Pipeline

Cleaned and aligned anonymized high-frequency tick data with Python, Pandas and Polars, then turned it into repeatable feature and evaluation workflows.

使用 Python、Pandas 与 Polars 清洗和对齐高频 Tick 数据,形成可重复的特征与评估流程。
PRACTICEDB—02

API Integration

Coordinated front-end and API integration for Lens Agent in a 48-hour sprint, clarified interface states and helped shorten integration time by 30%.

在 Lens Agent 项目中推动前端与接口联调、梳理接口状态,联调时间缩短 30%。
PRACTICEDB—03

AI Workflow

Use AI-assisted analysis and human review as a workflow: structure inputs, inspect outputs and keep the final decision explainable.

将 AI 辅助分析与人工复核组织为工作流,关注输入结构、输出检查与可解释性。
CURRENT FOCUSB—04

Backend Systems

Deepening service boundaries, data models, task state, logging, failure recovery and LLM tool workflows.

正在深化服务边界、数据模型、任务状态、日志、失败恢复与 LLM 工具工作流。

03 / SELECTED WORK

Quant Canvas

The first three cards are research directions. Lens Agent is a completed 48-hour delivery and is presented separately as verified execution.

前三项为研究方向;Lens Agent 是已完成的 48 小时交付项目。
Factor Signal Lab concept visual

RESEARCH DIRECTION

Factor Signal Lab

A reproducible flow for market data, feature construction, chronological validation and cost-aware evaluation.

市场数据、特征构建、时序验证与交易成本评估流程。
Risk and Drawdown Engine concept visual

RESEARCH DIRECTION

Risk & Drawdown Engine

An interpretable monitoring layer for volatility, correlation, drawdown, allocation and exposure.

围绕波动率、相关性、回撤、配置与组合暴露的可解释监测层。
Alternative Data Pipeline concept visual

RESEARCH DIRECTION

Alternative Data Pipeline

A bridge from behavioral insight to alternative-data cleaning, signal definition and model evaluation.

从用户行为洞察到另类数据清洗、信号定义与模型评估。
Ray presenting Lens Agent at Attrax Hackathon

VERIFIED DELIVERY · 2026

Lens Agent

Owned the interaction flow, high-fidelity interface and front-end implementation. Aligned front-end and backend states, data flow and API integration in a four-person team.

负责交互流程、高保真界面与前端实现,并在四人团队中推动接口状态、数据流和联调节奏对齐。
ENTERPRISE OS / MACAU

USER-CONFIRMED PROJECT

Macau Enterprise SaaS

Helped a Macau team build an enterprise full-stack SaaS, participating in requirement breakdown, product interface, front-end/backend collaboration and the end-to-end delivery flow.

协助澳门团队搭建企业全栈 SaaS,参与企业需求拆解、产品界面、前后端协作与完整交付流程。

04 / AWARDS

Evidence across
technology & art.

Two awards support the same profile: the ability to build with AI and the visual sensitivity to make technology legible and memorable.

两项奖项分别来自 AIGC 创新与数字艺术,体现技术实践与艺术审美的交叉能力。
TECHNOLOGY / 202602

South China
Second Prize

China Collegiate Computing Competition · AIGC Innovation Competition, Creator Track

《小时光》中国高校计算机大赛 AIGC 创新赛 · 创作赛道 · 华南赛区二等奖
DIGITAL ART / SPRING EDITION03

Third Prize

5th HKDADC Hong Kong Digital Art & Design Competition

EARTH WHISPERS第五届 HKDADC 香港数字艺术设计大赛春季赛 · 三等奖

05 / EXPERIENCE

Evidence in
numbers.

Metrics stay next to the work that produced them.每项数据都与对应经历放在一起。

Attrax Hackathon venue
ATTRAX × BEYOND EXPO / 2026
TOP 30%1.55 OOS SHARPE
< 7.8% MAX DRAWDOWN

2025

Paris Quant Challenge

Honorary Strategy Award

Built a cross-sector statistical-arbitrage strategy on anonymized Euronext Paris tick data using Python, Pandas, Polars, ADF and Engle–Granger tests.

基于欧洲泛欧交易所匿名高频 Tick 数据构建跨行业统计套利策略,获 Top 30% Finalist/策略优秀奖。
+27%CORE-PATH CLICKS
+45% MONTHLY REACH

2026

EMC Global

Cross-border E-commerce Operations

Built overseas brand visuals, improved web interaction and supported social strategy.

搭建海外品牌视觉、优化官网交互并支持社媒策略。
48H4-PERSON TEAM
2 HOURS EARLY

2026

Attrax Joint University Hackathon

Interaction & Front-end Development

Delivered the Lens Agent demo through rapid iteration, interface implementation and API coordination.

通过快速迭代、界面实现与 API 协作完成 Lens Agent 演示。
23—24PRODUCT OPERATIONS
COMMUNITY & EVENTS

2023—2024

LALA Company

Product Operations

Supported international art fairs, offline events, community engagement and content operations.

参与国际艺术书展、线下活动、社群与内容运营。

06 / CONTACT

Let’s build with
data & AI.

Open to quantitative research, AI product and backend engineering opportunities.期待量化研究、AI 产品与后端工程方向的机会。