LR8W4V6X | Quantitative Researcher Digital Assets & Algorithmic Trading

• Location: East of England
• Compensation: Competitive package

Job Highlights

• Pioneer cutting-edge quant strategies in the dynamic digital assets space.
• Work with massive datasets (on-chain, order books, pricing) to drive actionable insights.
• Collaborate with a high-caliber team to deploy and optimize algorithmic trading systems.
• Direct impact on risk-managed trading performance in fast-evolving markets.

Key Responsibilities

• Source, clean, and analyze digital assets data using Python/R/C++ and proprietary tools.
• Develop ML/statistical models for price prediction, arbitrage, and risk mitigation.
• Backtest and refine trading strategies under live market conditions.
• Implement real-time monitoring systems for strategy performance and risk thresholds.
• Research emerging blockchain technologies and regulatory shifts to inform strategy.

Must-Have Requirements

• STEM/Quant degree (Finance, Math, CS, Physics) from a top-tier university.
• 5+ years hands-on experience in quant trading/research, preferably in digital assets/Web3.
• Mastery of Python, C++, and data analysis libraries (Pandas, NumPy, TensorFlow).
• Proven track record in linear arbitrage and strategy backtesting.
• Mandarin fluency preferred; appetite for high-pressure, detail-driven environments.

How to Apply?

Click 'Apply'or send your resume to [] with the subject line [Apply to WBLR8W4V6X]. Refer a friend for this role and earn up to £500 in referral bonuses! See detailshttps://ttukoffer.co.uk/refer-a-friend-bonus/

量化研究员（数字资产方向）

• 工作地点: 东英格兰
• 薪资范围: 有竞争力的薪资

职位亮点

• 参与前沿数字资产量化策略开发，直面行业高增长领域。
• 处理海量链上/市场数据，构建高价值交易模型。
• 与顶尖团队协作，实战优化算法交易系统。
• 直接影响风险可控的交易决策，快速响应市场变化。

核心职责

• 使用Python/R/C++清洗、分析数字资产市场数据（价格/订单簿/链上数据）。
• 开发机器学习/统计模型，用于价格预测、套利及风险管理。
• 对交易策略进行历史回测及实时市场调优。
• 设计实时监控系统，跟踪策略表现与风险阈值。
• 研究区块链技术趋势及监管政策，指导策略迭代。

硬性要求

• 顶尖院校理工/量化专业背景（金融、数学、计算机、物理等）。
• 5年以上量化交易/研究经验，数字资产/Web3领域优先。
• 精通Python、C++及数据分析库（Pandas、NumPy、TensorFlow）。
• 具备线性套利策略开发及回测经验。
• 普通话流利者优先；适应高强度、高精度工作环境。

如何申请？

点击'Apply'申请或发送简历至[]，邮件标题注明[申请 WBLR8W4V6X]。推荐奖金：成功推荐人选可获得500英镑奖励。详情：https://ttukoffer.co.uk/refer-a-friend-bonus/

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