Quantitative Researcher – Equities

Marlin Selection Ltd; London; On-site; GBP 70,000 - 100,000; Full time

Job summary

A leading global investment firm in London is seeking a Quantitative Researcher to enhance their systematic equity strategies. This full-time role involves alpha research, model development, and collaboration within a dynamic team, targeting those with a quantitative background and programming skills in Python.

Qualifications

• Experience in Cash Equities: 3-5 years in equity research.
• Solid background in alpha research and systematic strategy development.
• Demonstrated ability to analyze diverse datasets.

Responsibilities

• Drive the research agenda, focusing on idea generation and backtesting.
• Analyze datasets and build predictive models for investment.
• Collaborate with the investment team ensuring alignment.

Skills

Programming in Python

Statistical learning techniques

Research experience in alpha research

Data analysis

Critical thinking

Education

Masters or PhD in a quantitative discipline

Job description

Location: London
Industry: Systematic Equity Strategies
Job Type: Full-Time, Permanent

Our Client:
We are partnering with a leading global investment firm based in London, renowned for its data-driven, innovative approach to equity research. They are seeking an experienced Quantitative Researcher to join their dynamic team, focusing on systematic equity strategies. This is a fantastic opportunity for a talented individual to contribute to cutting-edge alpha research and work with a team of like-minded experts in the field.

Key Responsibilities:

As a Quantitative Researcher, you will play a vital role in the development of alpha research for equity strategies. Your responsibilities will include:

• Alpha Research: Collaborating closely with the Senior Portfolio Manager (SPM) to drive the research agenda, with a primary focus on idea generation, data gathering, research/analysis, model implementation, and backtesting of systematic equity strategies.
• Model Development: Combining financial insights with advanced statistical learning techniques to analyze diverse datasets, build predictive models, and apply them to the investment process.
• Collaboration: Working alongside the SPM and investment team in a highly transparent environment, ensuring alignment throughout the investment lifecycle.

Required Technical Skills:

• Programming: Proficiency in Python for quantitative research, model building, and analysis.
• Academic Background: A Masters or PhD in a quantitative discipline such as Computer Science, Applied Mathematics, Statistics, or a related field from a top-ranked university.
• Research Experience: Solid background in alpha research and systematic strategy development.

Desired Experience:

• Experience in Cash Equities: 3-5 years of hands-on experience in equity research, specifically in alpha research for cash equities strategies.
• Data Expertise: Demonstrated ability to analyze fundamental, event-related, and alternative datasets, integrating this information into actionable insights for strategy development.

Highly Valued Skills & Experience:

• Strong economic intuition and the ability to apply critical thinking to complex financial problems.
• Previous involvement in statistical arbitrage strategies will be considered highly advantageous.

Why Join This Team?

This role provides a unique opportunity to work in a fast-paced, intellectually stimulating environment with access to diverse datasets and cutting-edge technology. You will be part of a collaborative team focused on deploying systematic strategies that impact the global equity markets.

If you are passionate about quantitative research, systematic trading, and want to work with a firm that thrives on collaboration and innovation, we encourage you to apply!

Can't find the job you're looking for, send us your info and we will review your options?

(Permitted file size is 5Mb and file types are: doc, docx, txt, pdf, rtf, xls)

Please complete the form below, your data is processed here under legitimate interest. Please also note that for your privacy no data from this form is stored in this website ( view our privacy policy ).