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Quantitative Researcher - Commodities

Millennium Management

London

On-site

GBP 60,000 - 100,000

Full time

30+ days ago

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An established industry player is seeking a Quantitative Researcher to join their innovative Quant Technology team. This role offers the opportunity to leverage your expertise in commodities market data and analytics to build next-generation tools that support traders and manage risk. You will collaborate with a global team, focusing on market positioning analytics, setting up data pipelines, and developing analytical models. If you thrive in a fast-paced environment and have a passion for data science and technology, this position is perfect for you to make a significant impact in the finance sector.

5+ years of experience with commodities futures market data.
Strong Python skills with practical knowledge of data science libraries.

Conduct Commodities Model Research and maintain project/code base.
Build analytical models and create visualization dashboards.

Python

Statistical Analysis

Data Science

Communication Skills

Detail Orientation

ETL Pipelines

Linux

Cloud Technologies

Data Visualization Tools (e.g., Plotly)

Quantitative Researcher - Commodities

Millennium is a top tier global hedge fund with a strong commitment to leveraging innovations in technology and data science to solve complex problems for the business. We are assembling a strong Quant Technology team to build our next generation in-house analytics, Trader & Risk support tools.

Responsibilities

Work as part of a global team doing Commodities Model Research, Data Exploration & Project/code base maintenance
Set up data pipelines, build analytical models & create visualization dashboards
Interact with broad group of stakeholders including senior portfolio managers, business and technology leadership
Role will focus on market positioning analytics

Requirements

Minimum 5 years of experience working with commodities futures market data and positioning data
Prior experience with ETL pipelines
Strong Python skills, practical knowledge of the python data science eco-system (numpy, pandas, jupyter, plotly, etc.)
Experience developing on a Linux-based platform, cloud experience an advantage
Good knowledge of Statistics and Data Science
Knowledge of any trading systems and Portfolio Management advantageous
Solid communications skills
Able to work independently in a fast-paced environment
Detail oriented, organized, demonstrating thoroughness and strong ownership of work

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