Machine Learning Researcher - Quantitative Trading- Leading Market-Maker / Hedge Fund

eFinancialCareers; Greater London; On-site; GBP 400,000 - 750,000; Full time

Benefits offered by this job

Shape ML direction

Proprietary datasets

Research freedom

Conferences

Compensation package

Work-life balance

Job summary

eFinancialCareers is seeking a talented ML specialist to join its quantitative research and trading technology teams in London. You will build and test models on large market data, extract signals, and develop trading strategies with a cross-asset scope.

You will work at the intersection of research, trading and software engineering, balancing cutting-edge experimentation with pragmatic, commercially useful solutions, in a highly collaborative environment.

Qualifications

• Deep ML expertise from 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.

Responsibilities

• Use ML to extract signals and insights from vast market datasets, analyze data, build and test models and develop trading strategies.
• Work at the intersection of quantitative research, trading and software engineering; time may be split between alpha generation and ML research.
• Collaborate across teams to maximise PnL and share insights.
• Explore how ML/AI can improve research, engineering and operations across the business.
• Maintain freedom to experiment with model architectures, feature transformations and hyperparameters, while making pragmatic decisions about approaches.

Skills

Deep ML

Programming

Quantitative problem-solving

Big data analysis

ML architectures

Collaboration & communication

Markets experience not required

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:

• 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.