Quantitative Researcher

Point72 Asset Management, L.P; London; On-site; GBP 60,000 - 80,000; Full time

Job summary

An innovative firm is seeking a Quant Researcher to join its new portfolio management team focused on systematic trading of equities. This role offers a unique chance to engage in the early stages of product development and contribute to a growing team. The ideal candidate will perform rigorous research to uncover market anomalies, develop alpha strategies, and enhance portfolio trading in a production environment. If you are a motivated individual with a strong analytical mindset and a passion for data science, this opportunity could be your next big career move.

Qualifications

• MS or PhD in a quantitative discipline required.
• Proven expertise in Python and handling large datasets.

Responsibilities

• Conduct innovative research to find systematic anomalies in equities.
• End-to-end development of alpha strategies and data processing.

Skills

Python

Data Science

Machine Learning

Feature Engineering

Research Abilities

Education

MS or PhD in a quantitative discipline

Tools

Data Processing Tools

Backtesting Frameworks

Job description

About Cubist

Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources.

Role:

A new Cubist portfolio management team specializing in the systematic trading of equities is looking for a Quant Researcher whose core focus will be working on mid-frequency alpha strategies. Joining the team will provide a unique opportunity to be involved with the early stages of a product launch and develop within a growing team.

Responsibilities:

• Perform rigorous and innovative research to discover systematic anomalies in the equities market
• End-to-end development, including alpha idea generation, data processing, strategy backtesting, optimization, and production implementation
• Identify and evaluate new datasets for stock return prediction
• Maintain and improve portfolio trading in a production environment
• Contribute to the analysis framework for scalable research

Requirements:

• MS or PhD in a quantitative discipline
• 0-2 years of professional work experience
• A background in financial markets is not necessary, but an interest in the field is essential
• Proven expertise in Python and handling large datasets
• Fluency in data science practices, e.g., feature engineering. Experience with machine learning is a plus
• Highly motivated, curious, and critical thinker
• Collaborative mindset with strong independent research abilities
• Commitment to the highest ethical standards