Junior Quantitative Investment Analyst

Role Overview

We have partnered with a leading Asset Manager looking to hire a Junior Quantitative Investment Analyst to join their front-office desk quant team, based in London. This is an entry-level opportunity for a recent graduate or intern-level candidate with strong quantitative skills, coding ability (Python), and an interest in financial markets.

The role will sit within a growing investment quant function supporting decision-making across asset classes. The successful candidate will contribute to the development of robust, scalable analytics, tools, and infrastructure while working closely with portfolio managers, investment strategists, and analysts. The position offers a strong learning curve and exposure to cross-asset investment thinking, with support from a collaborative and technically skilled team.

Key Responsibilities

• Contribute to quantitative analysis and research to improve investment processes and decision-making.
• Support the development and maintenance of Python- and Excel-based solutions used by the investment team.
• Assist in the development of internal quantitative libraries and platforms
• Help integrate infrastructure changes into analytical solutions.
• Work with engineering colleagues to test systems and ensure requirements are implemented correctly.
• Participate in broader investment and analytics projects in a collaborative and iterative team environment.

Requirements & Qualifications:

• Degree in a quantitative field (eg. Mathematics, Physics, Computer Science)
• Proficiency in Python, with strong coding and problem-solving ability.
• Demonstrated strength in at least 1-2 of the following areas:
• Coding and software development.
• Quantitative aptitude and modelling
• Foundational knowledge of financial markets (through studies or internships).
• Ability to communicate technical ideas clearly and work collaboratively within a team.
• High motivation, attention to detail, and eagerness to learn in a fast-paced environment.
• Internship or industrial placement experience in financial services or a quantitative role (preferred)
• Familiarity with databases (e.g., SQL or Hadoop) and visualisation tools such as Power BI (preferred)
• Exposure to investment concepts such as derivatives, asset-liability modelling, or portfolio risk analysis (e.g., VaR, stress testing).