Quantitative Researcher, High Frequency Trading

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

We are working with a machine learning focused high frequency trading firm. They trade crypto and equities, and on several of the exchanges where they're active they account for more than 1% of total volume. Their research runs on a cluster of thousands of GPUs.

They're hiring Quantitative Researchers who have already built signals or strategies in HFT or statistical arbitrage. The role is fully remote, and they're open to candidates in Europe, the US and Asia.

What you'll do

• 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

What they're looking for

• A track record of building signals or strategies in HFT or statistical arbitrage with a 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 just as relevant.
• The ability to talk through past results, within the limits of what you're allowed to share

What's on offer

• Base salary competitive with top HFT firms, plus a direct share of the P&L you generate
• Fully remote across Europe, the US and Asia
• Research compute at a scale few firms offer