Quantitative Researcher (PhD)

JR United Kingdom; London; On-site; GBP 60,000 - 100,000; Full time

Job summary

An innovative quantitative investment firm is on the lookout for a talented PhD Quantitative Researcher to join their dynamic team. This role is ideal for someone with a strong foundation in machine learning and a passion for financial markets. You will develop predictive trading strategies, conduct in-depth research, and collaborate with a team of experts to influence investment strategies. The firm offers a vibrant research-centric environment, competitive salary, and opportunities for mentorship and career development. If you're eager to make a significant impact in a fast-paced, data-driven setting, this is the perfect opportunity for you.

Benefits

Health Insurance

Pension Contributions

Mentorship Opportunities

Access to Cutting-edge Technology

Comprehensive Benefits Package

Qualifications

• PhD in Machine Learning, Computer Science, Mathematics, or Physics.
• Up to 2 years of experience in machine learning applied to finance.

Responsibilities

• Develop and deploy machine learning models for predictive trading strategies.
• Conduct research to uncover alpha-generating opportunities.

Skills

Machine Learning

Statistical Modelling

Python

C#

Data Analysis

Education

PhD in Quantitative Discipline

Tools

Data Pipelines

Market Simulators

Job description

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This successful quantitative investment firm harnesses cutting-edge machine learning and statistical techniques to navigate global financial markets. We are seeking a PhD Quantitative Researcher with up to 2 years of experience in machine learning to join our dynamic research team. This role is perfect for a technically adept candidate who excels at translating complex theories into practical solutions, pitching innovative ideas to senior stakeholders, and contributing to pioneering research efforts.

Responsibilities

• Develop and deploy machine learning models to create predictive trading strategies across diverse asset classes.
• Conduct in-depth research to uncover alpha-generating opportunities, leveraging advanced statistical and ML techniques to analyse complex financial datasets.
• Design, back-test, and implement robust trading algorithms optimized for live market environments.
• Build supporting tools, such as data pipelines and market simulators, to enhance research and strategy development.
• Effectively communicate intricate concepts, presenting alpha-generating strategies to senior traders and portfolio managers with clarity and impact.
• Collaborate closely with quantitative researchers, traders, and engineers to integrate models into high-performance production systems.

Technical Skills and Experience

• PhD in a quantitative discipline (e.g., Machine Learning, Computer Science, Mathematics, Physics, or related fields).
• Up to 2 years of experience in machine learning, preferably applied to financial markets, time-series analysis, or similar data-intensive domains.
• Deep theoretical knowledge of machine learning, with expertise in areas such neural networks and statistical modelling.
• Advanced programming proficiency in Python or C#, with a track record of writing production-ready code.
• Demonstrated ability to articulate complex ideas and pitch innovative strategies to senior stakeholders.
• Enthusiasm for financial markets and a collaborative mindset to thrive in a team-driven culture.

What’s on Offer

• Competitive salary based on experience, plus performance-based bonus.
• Comprehensive benefits package, including health insurance and pension contributions.
• A vibrant, research-centric environment where your ideas directly influence investment strategies.
• Access to cutting-edge technology, proprietary datasets, and advanced computational resources to fuel your ML research.
• Mentorship and career development opportunities within a top-tier systematic investment firm.

Apply Now: If you’re ready to make an impact in a fast-paced, data-driven investment firm, submit your CV and a cover letter detailing your relevant experience to [insert application link or email]. We look forward to exploring how your skills can drive our success.