Aspect Capital

Global systematic investment management firm

Quantitative Research Analyst

Quantitative ResearchUpdated on Nov 11

Full-timeLondon, UKNo salary listedHybrid

About the Job

Requirements

A top-class undergraduate degree in a numerate discipline such as mathematics, statistics, physics, engineering, operations research, or computer science.
Up to 3 years of relevant industry experience; candidates joining directly from academia are also welcome.
A strong understanding of probability, statistics, linear algebra, and machine learning, with the ability to reason from first principles rather than relying on black-box tools.
The ability to analyse and synthesise information to solve problems, question assumptions, challenge results constructively, test fundamentals, spot anomalies, recognise when a result is too weak to act on, and flag it.
Strong programming ability in Python or MATLAB.

Responsibilities

Research, develop, and maintain systematic investment models across a range of signals and asset classes.
Formulate and solve portfolio construction and optimisation problems.
Conduct rigorous statistical analysis of diverse input data for systematic investment strategies, test the robustness of results, and record assumptions and caveats.
Present findings and their limitations accurately.

Desired Qualifications

An MSc or PhD in a numerate discipline such as mathematics, statistics, physics, engineering, operations research, or computer science is ideal.
A background in optimisation is highly desirable, for example convex optimisation, linear and quadratic programming, or stochastic and numerical optimisation.
Hands-on experience applying machine learning methods such as gradient boosting, neural networks, or regularised regression to noisy, non-stationary data using scikit-learn, PyTorch, or similar is a plus, as is a solid grasp of overfitting, cross-validation, and out-of-sample testing.

Aspect Capital is an award-winning systematic hedge fund based in London. We manage over $9 billion of client assets. Research sits at the core of our investment process, playing a critical role in the success of our business.
The Role:
Our hypothesis-driven research spans a broad range of strategies, asset classes and markets across different regions, and supports multiple products across Trend Following, Absolute Return and Customised Solutions. We are looking for a Quantitative Researcher with strong technical foundations to join us. You will work in a dynamic, collegiate, multi-disciplinary research team on projects spanning model development, portfolio construction, risk management and market access.

Key Responsibilities:

Researching, developing and maintaining systematic investment models across a range of signals and asset classes
Formulating and solving portfolio construction and optimisation problems
Conducting rigorous statistical analysis of diverse input data for systematic investment strategies, testing the robustness of results and recording assumptions and caveats
Presenting findings and their limitations accurately

Your experience:

A top-class undergraduate degree, and ideally an MSc or PhD, in a numerate discipline such as mathematics, statistics, physics, engineering, operations research or computer science
Up to 3 years of relevant industry , we also welcome candidates joining directly from academia too
A strong understanding of core concepts in probability, statistics, linear algebra and machine learning, with the ability to reason from first principles rather than relying on black-box tools
The ability to analyse and synthesise information to solve problems, question assumptions, challenge results constructively (including your own), test fundamentals, spot anomalies, and recognise when a result is too weak to act on and flag it
Strong programming ability in Python or MATLAB
A background in optimisation is highly desirable, for example convex optimisation, linear and quadratic programming, or stochastic and numerical optimisation
Hands-on experience applying machine learning methods such as gradient boosting, neural networks or regularised regression to noisy, non-stationary data, using scikit-learn, PyTorch or similar, is a plus, as is a solid grasp of overfitting, cross-validation and out-of-sample testing

If this role sounds of interest, we would love to hear from you.

About the Company

Aspect Capital

Global systematic investment management firm

Aspect Capital is a global manager of systematic, quantitative investments that uses computer-driven research and technology to design and run investment strategies. Their models analyze data to guide trading and portfolio construction, enabling automated or semi-automated execution. They differentiate themselves through a strong research culture, a large tech-enabled team of over 120 and $8.0 billion in assets under management, and being a certified B Corp focused on balancing profit with social and environmental impact. Their goal is to grow their quantitative models and research capabilities while delivering steady, repeatable returns for clients, guided by people, culture, and responsible business practices.

Company size: 51-200
Company stage: Not listed
Total funding: Not listed
Headquarters: London, United Kingdom
Founded: 1997

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