Software Engineer, Research – Cumberland Systematic

Overview

As part of Cumberland Systematic, you will design and build the full stack supporting a global, high-availability quantitative trading operation. You collaborate with researchers and engineers to accelerate the research lifecycle, from data engineering to feature generation and analysis. You will integrate diverse data sources, including blockchains and exchanges, and ensure robust testing and maintainable code. This role offers hands-on impact in a fast-paced, innovation-driven environment with global reach.

Responsibilities

• Design, develop, test, document, and maintain software and infrastructure for quantitative financial research
• Accelerate the research lifecycle from data engineering to feature generation and analysis
• Integrate with diverse data sources such as blockchains, exchanges, and data vendors
• Test at unit, functional, and integration levels
• Work within a small team and independently with a strong user focus
• Provide on-call support as needed

Key requirements

• Python experience gained through professional experience
• Built complex systems in modern Python that are maintainable and safely refactorable
• Hands-on experience managing large, evolving timeseries data
• A working knowledge of type safety and type systems
• Strong verbal and written communication skills
• Strong internal motivation and a continual desire to learn
• strong communication
• self-motivation
• initiative
• Python
• C++
• timeseries data management

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