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Machine Learning Researcher - Quantitative Trading- Leading Market-Maker / Hedge Fund
Why This Role Stands Out
Leverage cutting-edge ML research to drive significant impact in quantitative trading at a leading market-maker, benefiting from a highly collaborative culture and substantial compensation. This hybrid role is ideal for ambitious researchers with a passion for data analysis and strategy development who are eager to grow their expertise in a dynamic, fast-paced environment. You'll be at the forefront of innovation, with the freedom to explore new approaches and contribute to a firm renowned for its technological prowess.
Quick Overview
Salary
£200k - £250k/yr
Seniority
Mid Senior
Employment type
Full Time
Work mode
Hybrid
Location
London, United Kingdom
Posted
1 week ago
Machine Learning
Job Description
Salary: £200-250k base + £200-500k bonus // All experience levels
Client:
One of the world's top quantitative market makers is expanding its Machine Learning and broader AI capabilities. Already a market leader, the firm has invested extensively in its data and research infrastructure in recent years and is continuing to grow its ML teams to stay at the forefront of the industry.
As a cross-asset liquidity provider, the firm executes huge volumes of trades every day and works with enormous datasets, creating an unusually rich and fast feedback environment for applying Machine Learning to real-world problems.
Role:
You'll use Machine Learning to extract signals and insights from vast datasets of market data, analysing data, building and testing models and developing new trading strategies.
The work sits at the intersection of quantitative research, trading and software engineering. Depending on your interests and expertise, your time could be split between alpha generation within a trading team and broader ML research across the firm.
The environment is extremely collaborative, with research and discoveries shared across teams to maximise PnL collectively. For example, insights developed while working with an FX trading team may have applications within Equities or other asset classes.
Beyond direct trading applications, the firm is also exploring how the latest developments in ML and AI can improve research, engineering and operational workflows across the business.
You'll have significant freedom to experiment with model architectures, feature transformations and hyperparameters, while being expected to understand why techniques work and make pragmatic decisions about which approaches are appropriate for a particular problem.
Requirements:
Benefits:
Whilst we carefully review all applications, to all jobs, due to the high volume of applications we receive it is not possible to respond to those who have not been successful.
Contact
If you feel you're suitable for this role, want to hear about similar positions, or would like help hiring similar developers for your company, please send your CV or get in touch:
Richard Allan
richard.allan@oxfordknight.co.uk
+44 (0) 20 3137 9574
linkedin.com/in/richardallanok/
Client:
One of the world's top quantitative market makers is expanding its Machine Learning and broader AI capabilities. Already a market leader, the firm has invested extensively in its data and research infrastructure in recent years and is continuing to grow its ML teams to stay at the forefront of the industry.
As a cross-asset liquidity provider, the firm executes huge volumes of trades every day and works with enormous datasets, creating an unusually rich and fast feedback environment for applying Machine Learning to real-world problems.
Role:
You'll use Machine Learning to extract signals and insights from vast datasets of market data, analysing data, building and testing models and developing new trading strategies.
The work sits at the intersection of quantitative research, trading and software engineering. Depending on your interests and expertise, your time could be split between alpha generation within a trading team and broader ML research across the firm.
The environment is extremely collaborative, with research and discoveries shared across teams to maximise PnL collectively. For example, insights developed while working with an FX trading team may have applications within Equities or other asset classes.
Beyond direct trading applications, the firm is also exploring how the latest developments in ML and AI can improve research, engineering and operational workflows across the business.
You'll have significant freedom to experiment with model architectures, feature transformations and hyperparameters, while being expected to understand why techniques work and make pragmatic decisions about which approaches are appropriate for a particular problem.
Requirements:
- Deep Machine Learning expertise from either an applied or academic environment
- Strong programming and quantitative problem-solving skills
- Experience analysing large datasets and building/testing ML models
- Broad understanding of modern ML techniques and model architectures
- Ability to balance cutting-edge research with pragmatic, commercially useful solutions
- Collaborative nature with excellent communication skills
- Trading or financial markets experience is not required
Benefits:
- Help shape the firm's future ML direction and, to an extent, developments across the wider quantitative trading industry
- Work with enormous proprietary datasets in a rapid-feedback trading environment
- Significant freedom to research and experiment with new ML techniques
- Opportunities to attend leading academic and industry conferences
- Excellent compensation package
- Good work-life balance
Whilst we carefully review all applications, to all jobs, due to the high volume of applications we receive it is not possible to respond to those who have not been successful.
Contact
If you feel you're suitable for this role, want to hear about similar positions, or would like help hiring similar developers for your company, please send your CV or get in touch:
Richard Allan
richard.allan@oxfordknight.co.uk
+44 (0) 20 3137 9574
linkedin.com/in/richardallanok/
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