Quantitative Researcher

Hikaros Quant Lab (HQL) is a quantitative research and technology lab focused on solving difficult problems in financial markets through mathematics, statistics, machine learning and computation.

We are assembling a small, highly selective research team and are looking for exceptional problem-solvers who want to work at the frontier of quantitative research.

We are particularly interested in people whose expertise comes from mathematics, statistics, machine learning, physics, computer science, scientific computing or other research-intensive disciplines. We believe exceptional research ability is transferable: the financial domain can be learned; rigorous thinking, curiosity and the ability to discover something genuinely new are much harder to teach.

You will join at an unusually early stage and help shape the research organisation from the ground up.

There are no inherited research strategies, legacy models or established playbooks to follow. You will have the freedom to formulate hypotheses, develop new approaches, run experiments and determine which ideas are worth pursuing.

Your work involves:

• Developing statistical and mathematical models for complex predictive problems
• Applying machine learning and deep learning to large-scale datasets
• Investigating novel approaches to time-series prediction and representation learning
• Designing experiments and testing hypotheses through rigorous empirical research
• Building simulation and backtesting frameworks
• Working with large-scale data and computational infrastructure
• Translating promising research into robust, systematic investment strategies
• Exploring new applications of AI, optimisation and scientific computing

We're interested in exceptional problem-solvers rather than a particular industry background. Relevant backgrounds could include:

• Mathematics
• Statistics / Biostatistics
• Computer Science
• Machine Learning / AI
• Physics
• Operations Research / Optimisation
• Computational Science
• Applied Mathematics
• Other highly quantitative disciplines

You might be:

• A PhD student or recent PhD graduate
• An experienced researcher in AI, machine learning, scientific computing or another technical field
• A strong undergraduate or Master's graduate with exceptional academic results
• A researcher or engineer coming from another research-intensive industry
• An exceptional competitive mathematician, programmer or scientist

• Exceptional mathematical and statistical problem-solving ability
• Strong programming skills
• Intellectual curiosity and an ability to conduct independent research
• The ability to move between theory, experimentation and implementation
• An exceptional academic or competitive track record

You do not need to know how financial markets work. The team can teach the domain; the priority is finding people with exceptional raw research ability.

• You'll be joining at the very beginning of the build rather than entering an established research organisation.
• The firm is deliberately building a small, talent-dense team where researchers can take ideas from inception through to implementation without layers of infrastructure or organisational complexity.
• Researchers will have access to petabyte-scale datasets, GPU-accelerated training and large-scale simulation, with significant resources available to test ambitious ideas.
• Although trading is the initial application, the longer-term ambition extends beyond trading alone, using the technology, research and team being built to tackle a broader set of problems across AI, finance and technology.