Quantitative Researcher: Build Edge with Data & ML

Graviton Research Capital LLP; Amsterdam; Remote; EUR 107,000 - 160,000; Full time

Job summary

Graviton Research Capital LLP is seeking a Quantitative Researcher for 2027 graduates to join our global team across Amsterdam, London, New York and Singapore. You will investigate market behavior, develop quantitative models, and test hypotheses that translate into trading signals, working with researchers and technologists to push ideas into production.

The role rewards rigorous mathematical thinking, strong programming ability in Python and/or C++, and a structured approach to experiments in

Qualifications

• Degree in a quantitative discipline such as mathematics, physics, computer science, statistics, operations research or machine learning.
• Strong programming skills in Python and/or C++.
• Solid grounding in probability, statistics, linear algebra and optimization, with experience in machine learning or data analysis.

Responsibilities

• Discover predictive patterns and sources of alpha from billions of market events.
• Formulate hypotheses about market behaviour and design experiments to test them.
• Apply probability, statistics, optimization and machine learning to build predictive models and signals.
• Design robust backtests and statistical tests to distinguish signals from noise.
• Work with large datasets to uncover patterns not immediately visible.
• Collaborate with technologists to translate research ideas into production systems.

Skills

Python

C++

Probability

Statistics

Machine learning

Data analysis

Education

Quantitative degree (math/physics/CS/stat/OR/ML)

Job description

Graviton Research Capital LLP is seeking a Quantitative Researcher for 2027 graduates to join our global team across Amsterdam, London, New York and Singapore. You will investigate market behavior, develop quantitative models, and test hypotheses that translate into trading signals, working with researchers and technologists to push ideas into production.

The role rewards rigorous mathematical thinking, strong programming ability in Python and/or C++, and a structured approach to experiments in