Quantitative Researcher - Oil & Gas

Qenexus; Paris; Sur place; EUR 50 000 - 100 000; Plein temps

Résumé du poste

A newly launched trading team in Paris seeks a Quantitative Researcher specializing in Oil & Gas. In this role, you will collaborate with the Portfolio Manager to research and develop alpha strategies, leveraging large datasets to uncover statistical patterns and design production-ready signals. Ideal candidates will have advanced quantitative degrees and strong backgrounds in statistical analysis and machine learning.

Qualifications

• Strong background in statistical analysis, particularly with time series data.
• Experience with large, unstructured datasets in commodities or energy markets.
• Ability to manage multiple research streams simultaneously.

Responsabilités

• Leverage diverse datasets to uncover statistical patterns.
• Collaborate with researchers to improve methodologies and workflows.
• Monitor model performance and adapt strategies as market dynamics evolve.

Connaissances

Statistical analysis

Machine learning

AI techniques

Attention to detail

Intellectual curiosity

Formation

Advanced degree in quantitative discipline

Outils

Python

R

MATLAB

C++

C#

Description du poste

Our client, a newly launched trading team in Paris, hope to hire a Quantitative Researcher specialising in Oil & Gas.

In this role, you will work alongside the Portfolio Manager to research & develop alpha strategies.

Responsibilities :

• Leverage large, diverse datasets—including physical commodity data, supply / demand indicators, shipping flows, weather patterns, and macroeconomic variables—to uncover statistical patterns.
• Collaborate closely with other researchers to refine methodologies, exchange insights, and improve research workflows.
• Design and implement signals within a robust global execution framework, ensuring they are production-ready and scalable.
• Continuously monitor model performance and adapt strategies as market dynamics evolve.
• Own the full research lifecycle—from hypothesis generation and signal development to backtesting, implementation, and live deployment.

Requirements :

• Advanced degree in a quantitative discipline such as data science, statistics, mathematics, physics, or engineering.
• Strong background in statistical analysis, machine learning, or AI techniques—especially as applied to time series or macro / commodity data.
• Experience working with large, unstructured datasets across varying timeframes, ideally within commodities or energy markets.
• Proficient in at least one major programming language (Python, R, MATLAB, C++, or C#).
• Exceptional attention to detail and the ability to manage multiple research streams simultaneously.
• Intellectual curiosity and creativity in approaching complex problems, particularly around integrating unconventional data sources.