Remote HFT Quantitative Researcher — ML Signals & P&L Share

QNT Partners; Greater London; Remote; GBP 120,000 - 210,000; Full time

Job summary

QNT Partners is hiring Quantitative Researchers to develop predictive signals and strategies for high frequency trading in crypto and equity markets. The role emphasizes applying machine learning to large-scale market data and taking ideas from backtest to live trading with full ownership of performance.

The team collaborates with engineering on features, execution, and latency. A track record in HFT or statistical arbitrage, strong Python skills, and optional C++ experience are highly valued,

Qualifications

• Track record building signals or strategies in HFT or stat arb with Sharpe of 2.5 or higher.
• Experience applying machine learning to high-frequency market data.
• Strong Python; C++ is a plus.
• Crypto experience is useful but not essential; strong equities HFT or stat arb backgrounds are also relevant.
• Ability to discuss past results within the limits of what you're allowed to share.

Responsibilities

• Research and build predictive signals and strategies for high frequency trading in crypto and equity markets.
• Apply machine learning to large-scale market microstructure data.
• Take strategies from idea through backtest to live trading, and own their performance once live.
• Work with engineering on features, execution and latency.

Skills

Python

C++

ML

HFT background

Job description

QNT Partners is hiring Quantitative Researchers to develop predictive signals and strategies for high frequency trading in crypto and equity markets. The role emphasizes applying machine learning to large-scale market data and taking ideas from backtest to live trading with full ownership of performance.

The team collaborates with engineering on features, execution, and latency. A track record in HFT or statistical arbitrage, strong Python skills, and optional C++ experience are highly valued,