Quantitative Trading Analyst
LondonOn-siteFull-time
AI Summary
Develop scalable Python-based analytics tools and automated workflows to transform raw trading data into actionable insights for portfolio managers and committees, while researching and improving quantitative trading strategies.
About this role
Maven is a market-leading proprietary trading firm deploying its own capital across discretionary, systematic, and market-making strategies. Backed by deep expertise in trading, technology, and research, we are relentlessly focused on improving liquidity across global listed derivatives. Through advanced execution and pricing technologies, we improve how financial markets operate.
Responsibilities:
- Develop Advanced Analytics Infrastructure: Engineer scalable Python-based libraries and tools that standardize performance metrics across the group. create automated workflows that convert raw trading data into high-value insights for Portfolio Managers and the Investment Committee.
- Conduct Quantitative Strategy Research: Perform rigorous statistical analysis on trade and portfolio-level data to decompose PnL drivers. Identify alpha decay, parameter inefficiencies, and execution drag to deliver actionable research that directly improves performance.
- Improve Returns on Existing Strategies: Analyze performance on a trade and strategy level to identify inefficiencies of optimisation areas. Deliver recommendations backed by data and maintain follow through.
- Highlight Trading Risks & Opportunities: monitor portfolio exposures, performance trends, and market signals to highlight emerging risks and identify underutilized or mispriced opportunities across various strategies.
- Support Strategy Development: support the PM onboarding process, and business development initiatives into new product groups and strategies.
Candidate Specifications:
- At least 2–5 years of experience specifically within a Hedge Fund, Proprietary Trading Firm, or Quantitative Asset Manager.
- Strong proficiency in Python (Pandas, NumPy, SciPy) for data analysis and simulation; SQL knowledge is essential.
- Deep understanding of the trade lifecycle and buy-side strategies (e.g., Relative Value, Stat Arb, Volatility).
- Excellent communication and teamwork skills
- Ability to demonstrate wider interest in financial markets
- Outstanding numerical skills
- Proactive interest in improving existing trading strategies and identifying new opportunities
- Ability to take a high level of responsibility in an expanding, highly successful firm
- Excellent attention to detail
- Fast problem-solving skills
What We Offer:
- A great environment whereby technology is key to our success
- The upside of a start-up without the associated risks
- Friendly, informal and highly rewarding culture
- A fast-growing global firm with plenty of opportunities where you will have a significant impact
Skills
Algorithmic TradingAutomationBacktestingData AnalysisData EngineeringData PipelinesExecution AnalyticsNumPyPandasPerformance AttributionPortfolio AnalyticsPythonQuantitative ResearchRisk MonitoringSciPySimulationSQLStatistical AnalysisTrade Lifecycle
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