Quantative Researcher

Overview

We are partnering with a fast-growing European fintech business that is expanding its internal trading capability and looking to hire a Quant Researcher into its London-based team.
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This is a mid-level role suited to someone with around 2–5 years of experience in quantitative research, systematic trading, market making, or a related trading environment. The successful candidate will work closely with senior trading and technology stakeholders to help develop trading strategies, improve risk processes, and build scalable research infrastructure.
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The Role

Our client is investing heavily in its internal trading and execution platform as part of a broader strategy to enhance access to financial markets for retail investors. The Quant Researcher will play a key role in designing, testing, and improving systematic strategies, with an initial focus on equities and scope to expand across further asset classes over time.
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This is a hands-on research role within a small, high-impact team, offering the opportunity to contribute directly to trading, pricing, hedging, and risk management initiatives.
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Key Responsibilities

• Develop, test, and refine systematic trading strategies in a mid-frequency equities environment
• Build and improve models for pricing, hedging, inventory management, and execution
• Support the development of risk management frameworks, analytics, and tooling
• Design and maintain research infrastructure, including backtesting systems and data pipelines
• Work with large market datasets to identify predictive signals and trading opportunities
• Collaborate with trading, engineering, and product teams to help scale the firm’s trading capabilities
• Contribute to future modelling initiatives across additional asset classes
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Required Experience

• 2–5 years’ experience in a quantitative research, systematic trading, market making, or quant fund environment
• Strong experience in feature engineering and predictive modelling
• Solid understanding of systematic strategies and risk management principles
• Hands-on equities experience
• Strong programming skills in Python, Java, or R
• Experience working with market data, trading models, or research platforms
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Desirable Experience

• Exposure to market microstructure
• Experience within retail flow, brokerage, market making, or electronic trading environments
• Familiarity with trading technology stacks, optimisation tools, or risk systems
• Advanced degree in mathematics, statistics, physics, computer science, engineering, or another quantitative discipline
• Comfortable operating in a small, entrepreneurial team where processes and systems are still being built

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