Competitive
London, England
Permanent, Variable

Quantitative Researcher - Commodities

Posted by Indotronix Avani UK, Ltd..

Commodities Quantitative Researcher

A leading Hedge Fund is looking for an experienced Quant Researcher to join their collaborative, and entrepreneurial systematic investment team. They are seeking a strong commodities quantitative researcher to join in developing new signals and strategies. This opportunity provides a dynamic and fast-paced environment with excellent opportunities for career growth.

Job Description

Quantitative Researcher as part of a small, collaborative systematic global macro team with a focus on applying cutting edge techniques to strategies across the commodities, fixed income, and FX space.

Location

London or Switzerland

Principal Responsibilities

Identify and onboard new global markets and datasets

Analyze and manipulate large and diverse data sets for idea generation and alpha research with a focus on the commodities space

Research and develop signals, leveraging a variety of market and fundamental datasets, to be deployed in systematic trading strategies

Collaborate with the Senior Portfolio Manager and team in a transparent environment, engaging with the whole investment process from idea generation through execution with a focus on the Global Commodities space

Preferred Technical Skills

Strongly skilled in Python

Experience programming in C is a plus

Bachelor, Master's, or PhD degree in Computer Science, Engineering, Applied Mathematics, Statistics or related STEM field

Excellent communication, analytical, and problem-solving skills

Preferred Experience

2-4 years of experience working in a quantitative research capacity with a focus on Ags, Energy, Metals, Fixed Income, FX, or Equity Index strategies

Experience working with large and diverse data sets, specifically data sets associated with the commodity markets

Commodities market experience modeling futures curves and/or cross-market relationships

Highly Valued Relevant Experience

Experience in quantitative, econometrics, asset pricing, or macro sub-fields

Experience with machine learning, statistical techniques and related libraries