Quant Research Trainee: Global Markets & Strategy

Societe Generale; Singapore; Presencial; SGD 90.000 - 130.000; Jornada completa

Descripción de la vacante

Societe Generale in Singapore seeks a quantitative researcher to assist in creating and validating models for analysing financial markets, focusing on return and risk perspectives. You will contribute to research efforts with rigorous mathematical reasoning and emphasis on reproducibility.

You will automate workflows, maintain data visualization tools, and apply methodological care to avoid unverified procedures, while leveraging derivatives knowledge when relevant.

Formación

• Strong programming skills in Python or R and ability to write clear, reproducible code.
• Solid mathematical foundation with emphasis on probability, statistics, optimisation and linear algebra.
• Experience or familiarity with financial markets and derivatives is advantageous.

Responsabilidades

• Assist in the creation, testing, and documentation of quantitative models for analysing financial markets from both a return and risk perspective.
• Apply rigorous mathematical reasoning, ensuring that derivations, assumptions, and methodological choices are clearly stated and reproducible.
• Contribute to research projects requiring careful validation, sensitivity analysis, and clear separation of known, inferred, and uncertain components.

Conocimientos

Python

R

Mathematics

Financial markets

Communication

Documentation

Version control

Educación

Bachelor’s degree

Masters preferred

Quantitative field

Herramientas

Git

Descripción del empleo

Societe Generale in Singapore seeks a quantitative researcher to assist in creating and validating models for analysing financial markets, focusing on return and risk perspectives. You will contribute to research efforts with rigorous mathematical reasoning and emphasis on reproducibility.

You will automate workflows, maintain data visualization tools, and apply methodological care to avoid unverified procedures, while leveraging derivatives knowledge when relevant.