Equity Execution Quant within a Pod, Tier 1 Proprietary Trading Firm, London
Equity Execution Quant within a Pod, Tier 1 Proprietary Trading Firm, London
A successful trading team at a tier-1 proprietary trading firm in London are looking for an equity execution quant to join their pod in London. The team trade mid-high frequency machine learning strategies for European cash equity markets. They focus on using ML techniques i.e. decision path trees to extract alpha on the market. Their track record over the last 5 years is far ahead of many competitors.
As they have scaled, they are looking for an equity execution quant, to help them design and implement execution algorithms. This will include market impact analysis and taking ownership of optimal execution strategy. It's a 5 person team, so you will get exposure to the alpha research and portfolio construction aspects and be expected to help in those areas when needed.
The ideal candidate will come from an equity execution quant team (either buy-side or sell-side) and be strong in python.
Key Responsibilities:
- Develop, test, and implement execution models for cash equity markets. I.e. market impact modelling, time sliced execution (sequences of child orders), post trade analysis.
- Analyze large datasets to identify patterns and insights that can enhance trading strategies.
- Collaborate with traders, software developers, and other researchers to integrate models into the trading platform.
- Continuously monitor and improve model performance based on market conditions and feedback.
Qualifications:
- Advanced degree (Master's or PhD) in a quantitative field such as Mathematics, Statistics, Computer Science, or Financial Engineering.
- Strong programming skills in Python
- Knowledge of market microstructure in financial markets, particularly cash equity markets.
- Excellent problem-solving skills and attention to detail.
- Ability to work effectively in a team-oriented environment.
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