Quantitative Researcher, High Frequency Trading

QNT Partners; Greater London; À distance; GBP 136 000 - 211 000; Plein temps

Avantages offerts par ce poste

Direct share of P&L you generate

Fully remote across Europe, the US and

Asia

Résumé du poste

QNT Partners is seeking a talented Quantitative Researcher to design and deploy predictive signals for high-frequency trading in crypto and equity markets. You will own ideas from backtest to live trading, collaborating with engineering on features, latency, and execution.

We value proven ML on large-scale market data, strong Python, and ideally C++. This fully remote role welcomes applicants from Europe, the US and Asia, offering scale research compute and a direct share of the P&L you generate.

Qualifications

• Track record of building signals/strategies in HFT or statistical arbitrage.
• Experience applying ML to high-frequency market data.
• Strong Python; C++ is a plus.
• Crypto experience is useful but not essential.

Responsabilités

• 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.

Connaissances

Python

C++

ML

HFT

Outils

CUDA

Description du poste

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