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量化加密货币与美股交易员 / Quantitative Trader

Role overview

Qualifications

  • Based in Hangzhou with 2+ years in quantitative research or systematic trading.
  • Strong Python, SQL, statistics, and time-series skills.
  • Able to explain one strategy from hypothesis and data through validation and live outcomes.
  • Practical understanding of overfitting, leakage, market impact, and risk budgeting.

Responsibilities

  • Research and implement statistical, factor, event-driven, or market-making strategies.
  • Clean market data and build leakage-resistant backtests and robustness checks.
  • Model slippage, fees, capacity, turnover, drawdown, and tail risk.
  • Monitor live performance and diagnose gaps between research and execution.

About the company

Kirin logo

Kirin

Food & Beverage Manufacturing

We conduct research and trade alternative investment markets. Mathematicians, software engineers, and data scientists welcome.

Company details

IndustryFood & Beverage Manufacturing
Company size11 - 50

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Job description

我们正在杭州招聘一名量化交易员,负责加密货币和美股的策略研究、回测、执行监控和风险管理。我们重视可重复的研究、现实的交易成本和严格的风险纪律。

工作职责

• 研究并实现统计、因子、事件驱动或做市策略。

• 清洗市场数据,建立无泄漏的回测和稳健性测试。

• 评估滑点、手续费、容量、换手、回撤和尾部风险。

• 监控实盘表现,定位研究与执行之间的偏差。

• 与工程师共同改进数据、模拟、执行和风险基础设施。

任职要求

• 常驻杭州,2 年以上量化研究、系统化交易或相关经验。

• 熟练使用 Python、SQL、统计方法和时间序列分析。

• 能展示一个完整策略从假设、数据、验证到实盘结果的过程。

• 理解过拟合、数据泄漏、市场冲击和风险预算。

English

We are hiring a Quantitative Trader in Hangzhou to research, test, monitor, and risk-manage strategies across crypto and US equities.

Responsibilities

• Research and implement statistical, factor, event-driven, or market-making strategies.

• Clean market data and build leakage-resistant backtests and robustness checks.

• Model slippage, fees, capacity, turnover, drawdown, and tail risk.

• Monitor live performance and diagnose gaps between research and execution.

• Improve data, simulation, execution, and risk infrastructure with engineers.

Requirements

• Based in Hangzhou with 2+ years in quantitative research or systematic trading.

• Strong Python, SQL, statistics, and time-series skills.

• Able to explain one strategy from hypothesis and data through validation and live outcomes.

• Practical understanding of overfitting, leakage, market impact, and risk budgeting.

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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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