Data Scientist - Commodities

Q-Tx LLC, based in Houston, Texas, is an independent commodities trading business, leveraging our passion for data, research, technology and trading expertise to deliver consistent and high-quality returns for our investors.

Q-Tx is affiliated with Qube Research and Technologies, a global quantitative and systematic investment manager.

We are looking for an exceptional Data Scientist to join the Data Search & Analytics team. In this role, you will work between the Research and Trading desks, and the Engineering team to ensure the successful leveraging of data at the firm.

• Collaborating with the trading desk to design and implement their data pipelines
• Collaborating with data engineers to onboard relevant datasets for the desk within Q-Tx
• Implementing data transformations to produce high added-value datasets used for investment decisions
• Prototyping and designing code to extract, clean, and aggregate data from a wide range of raw sources and formats
• Managing the end-to-end process of onboarding new datasets
• Proactively solving data related problems to minimise time to production
• Innovating and experimenting with novel data extraction methods to enhance the firm’s data onboarding toolkit

• 3+ years of experience as a Data Scientist (or similar position); experience in a buy-side quantitative finance role is advantageous
• Postgraduate degree in a quantitative discipline such as Mathematics, Physics or Engineering
• Advanced programming experience in Python, including proficiency with data handling libraries such as Pandas and Num Py
• Demonstrable interest in financial markets and the application of data in its analysis and understanding
• Experience working with both traditional and alternative financial datasets
• Excellent communication skills, with the ability to effectively collaborate with all stakeholders, including researchers, traders, engineers, management, and external vendors
• Ability to work in a high-performance, high-velocity environment

Mid‑Senior level

Full‑time

Information Technology