The role involves developing analytics infrastructure in Python, conducting quantitative research, analyzing trading strategies, and supporting portfolio management and business development initiatives.
About Maven
Maven Securities is a technology-driven proprietary trading firm trading its own capital across options market making, high-frequency, and multi-strategy discretionary strategies — from London, Amsterdam, and offices across the US and Asia. We combine deep trading, technology, and research expertise to improve liquidity across global listed derivatives, with AI embedded in how we operate day to day.
The RoleAs a Quant Trading Analyst within our Market Intelligence team, you will sit at the intersection of research, technology, and trading. You will turn raw trading data into high-value insights, build the analytics and AI tooling that Portfolio Managers (PMs) rely on daily, and deliver data-backed recommendations that materially and measurably improve PnL. This is a high-impact, high-ownership role for someone who wants their analysis to translate directly into trading performance.
What You Will DO- Improve returns on existing strategies - Analyse performance at trade and strategy level, deliver data-backed recommendations to PMs, and maintain follow-through to implementation and outcome measurement. Success is quantifiable, recorded, and tied to material PnL improvement - not one-off analysis.
- Build analytics infrastructure & AI tooling for PMs - Develop and standardise tools that generate high-value insights, and establish an AI foundation that accelerates PMs' day-to-day decision-making, working with Support and Technology teams where appropriate.
- Drive quantitative strategy research - Build a trading framework applied across multiple global strategies, identify style drift early and escalate to PMs and the HoMI, and document research in a reproducible format.
- Create synergies and global engagement - Develop strong dialogue across the Market Intelligence team and build proactive, positive relationships with PMs that deepen engagement and adoption of market intelligence tooling.
- Develop advanced analytics infrastructure - Engineer scalable Python-based libraries and tools that standardise performance metrics across the group, and create automated workflows that convert raw trading data into insights for PMs and the Investment Committee.
- Conduct quantitative strategy research - Perform rigorous statistical analysis on trade- and portfolio-level data to decompose PnL drivers, and identify alpha decay, parameter inefficiencies, and execution drag to deliver actionable research.
- Improve returns on existing strategies - Identify inefficiencies and optimisation areas, deliver recommendations backed by data, and maintain follow-through to outcomes.
- Highlight trading risks & opportunities - Monitor portfolio exposures, performance trends, and market signals to surface emerging risks and identify underutilised or mispriced opportunities across strategies.
Essential
- 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).
- Outstanding numerical skills and excellent attention to detail.
- Fast problem-solving skills and excellent communication and teamwork.
Highly valued
- An understanding of how AI can support role-specific responsibilities while maintaining appropriate governance and compliance.
- Proactive interest in improving existing strategies and identifying new opportunities.
- Ability to take a high level of responsibility in an expanding, highly successful firm.
- Demonstrable wider interest in financial markets.
- Competitive compensation package
- Annual discretionary bonus
- Group pension plan
- Enhanced annual leave allowance after 2+ years’ service
- 25 days’ annual leave (plus public holidays)
- Fully catered breakfast, lunch, and snacks prepared by an in-house chef
- Private healthcare and life assurance
- On-site private gym with instructor-led classes including boxing, yoga, and more
- Monthly company events and social activities
- Work in a forward-thinking environment where AI is integral to our strategy and daily operations
Maven Securities London, England Office
6 Bevis Marks, London, United Kingdom, EC3A 7
Similar Jobs
Fintech • Payments • Financial Services
Own the analytical and technical backbone of trading risk and fraud operations. Build production-grade infrastructure, monitoring tools, dashboards, and detection algorithms for toxic flow, latency arbitrage, and abusive trading. Investigate suspicious activity, assess product and promotion risks, classify clients for A-book/B-book decisions, and deliver solutions from data extraction through deployment. Improve automation, identify process gaps, report findings, and mentor junior analysts.
Top Skills:
PythonSQL
Fintech • Mobile • Payments • Software • Financial Services
Coordinate and execute risk-based internal audits across Finance and Treasury, including financial risk and regulatory obligations. Develop data-driven continuous monitoring and automated audit routines, assess governance and controls, track recommendation implementation, and collaborate with stakeholders across a multinational organization. The role also contributes to developing the internal audit methodology, team operations, and assurance framework.
Top Skills:
Automated Audit RoutinesContinuous MonitoringData Analytics
Fintech • Mobile • Payments • Software • Financial Services
Build governance and assurance foundations for Wise’s Risk Assessment platform. Develop data quality monitoring, contracts, lineage tracking, control validation, drift detection, audit trails, explainability tooling, and regulatory evidence generation. Integrate these capabilities with the Risk API and collaborate with Product and Financial Crime teams. The role requires designing high-throughput, reliable backend systems that make risk decisions trusted, explainable, auditable, and continuously monitored.
Top Skills:
JavaKafkaNoSQLSQL
What you need to know about the London Tech Scene
London isn't just a hub for established businesses; it's also a nursery for innovation. Boasting one of the most recognized fintech ecosystems in Europe, attracting billions in investments each year, London's success has made it a go-to destination for startups looking to make their mark. Top U.K. companies like Hoptin, Moneybox and Marshmallow have already made the city their base — yet fintech is just the beginning. From healthtech to renewable energy to cybersecurity and beyond, the city's startups are breaking new ground across a range of industries.
