Execution Strategy Quant (Cash Equities), Director in London

Execution Algorithm Design & Development

• Design, implement, and maintain production execution algorithms from scheduling models to adaptive allocation strategies driven by real-time signals and analytics.
• Build, enhance, and optimise venue selection, queue priority modelling, and dark/lit routing across fragmented equity markets.
• Develop and improve execution models that account for market impact, timing risk, and other key cost drivers.
• Leverage AI and machine learning tools across the development lifecycle, from accelerating research and prototyping to enhancing model validation, code review, and continuous performance monitoring in production.
• Develop and maintain client-specific algorithm customisations, respond to BAU and analytics requests, and lead investigations into order behaviour and execution performance queries raised by clients or internal stakeholders.

Quantitative Research & Signal Development

• Understand and study equity market microstructure: order book dynamics, venue behaviour, queue mechanics, adverse selection, and execution impact.
• Build and back-test models on tick-level and order-level data; translate findings into production components with measurable performance improvements.
• Model internal and external liquidity sources to optimise algo interaction across the full liquidity landscape.

Production Engineering & Delivery

• Write clean, efficient, production-quality code where latency, correctness, and resilience are non-negotiable.
• Own the full development lifecycle: design, testing, deployment, monitoring, and iteration based on live performance data.
• Build analytics and reporting tools to measure execution quality, identify performance gaps, and surface improvement opportunities.
• Contribute to platform architecture and scalability as volumes, markets, and complexity grow.

Collaboration & Stakeholder Engagement

• Partner with traders, electronic trading specialists, and technology teams to refine models and influence execution strategy in real time.
• Collaborate with Sales and Client Coverage to translate client execution needs into algorithmic enhancements and bespoke solutions.
• Work in close partnership with control functions such as Legal, Compliance, Market and Credit Risk, Audit, Finance to ensure appropriate governance and control infrastructure.

Culture, Risk & Compliance

• Build a culture of responsible finance, good governance and supervision, expense discipline and ethics.
• Be familiar with and adhere to Citi's Code of Conduct and the Plan of Supervision for Global Markets and Securities Services; and ensure that all team members understand the need to do the same.
• Adhere to all policies and procedures as defined by your role which will be communicated to you.
• Obtain and maintain all registrations/licenses which are required for your role, within the appropriate timeframe.
• Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behaviour, conduct and business practices, and escalating, managing and reporting control issues with transparency.

Qualifications

• 10+ years of experience in a comparable Algo Quant, Quantitative Developer or Strategist role, ideally in Cash Equities or FX but candidates with analogous experience in other areas are considered too.
• Strong technical and programming skills are essential, with proficiency in low latency and resilient Java or C++ required. Proficiency in Python and/or KDB+/q for tick data analytics and real-time signal computation is highly desirable.
• Exposure to market data and derived statistics and analytics is a plus.
• Proven experience in software architecture design and engineering principles, with a demonstrable track record of building systems where low latency and high throughput are crucial.
• Strong grounding in probability and statistics for quantitative inference, combined with a solid understanding of equity market microstructure, including the mechanics of limit order books, queue dynamics and priority, venue fragmentation across lit and dark pools, adverse selection, and market impact cost modelling.
• Master's or PhD in Engineering, Computer Science, Finance, Mathematics, or a related field is preferred. Strong candidates with a Bachelor's degree and relevant experience are also welcome to apply.

Role Summary

Citi's Electronic Execution & Algo Trading Quant team is seeking an experienced execution strategist to research, design, develop, and maintain the algorithmic trading systems that define Citi's execution product. You will be at the heart of a world-class electronic trading franchise, building the next generation of execution strategies, owning the full lifecycle from idea generation and research through implementation and testing to production deployment and continuous improvement. If you are the kind of person who wants to see your code running in live markets, your signals driving real execution decisions, and your models measurably improving outcomes for clients and the firm, this role was built for you.