Helix Junior Quantitative Developer

The opportunity would involve tackling complex problems in which you’d be a key part of a team working on a large breadth of challenges, including the following:

• Develop and support complex quantitative StatArb strategies involving large- scale data processing, sophisticated statistical modeling, portfolio construction, and highly optimized execution.
• Build and maintain systems handling highly diversified equity portfolios.
• Monitor transaction costs and the behavior of a high turnover strategy.
• Process and analyze vast historical datasets for research and back-testing, alongside real-time, tick-level market data for live trading.
• Contribute to the design and use of a high-performance, graph-based (DAG) framework enabling concurrent data processing for research and production.
• Monitor and manage execution quality, transaction costs, and market risks arising from changing market regimes and small statistical effects.
• Work closely with quantitative researchers to enhance tooling, frameworks, and shared feature libraries.
• Take ownership of system components in a fast-paced, agile environment, working both independently and collaboratively as required.
• Participate in live trading support, including interaction with orders and brokers as part of a rota (FCA certification required).

3 years’ experience in a technical role within the finance industry

• Degree in STEM subjects such as Computer Science, Maths, or Physics
• Python: Strong software developer with in-depth knowledge and experience.
• Numpy (including Numba): in-depth knowledge is required.
• Knowledge of Unix systems (processes, memory, I/O).
• Understanding of statistical methods, numerical optimization, and equity market microstructure.
• Experience working with graph-based (DAG) data processing frameworks.

• Highly analytical with a strong sense of ownership and accountability.
• Comfortable tackling complex, ambiguous problems with limited oversight.
• Collaborative mindset with the ability to work closely with researchers, technologists, and trading operations.
• Calm and reliable under pressure, particularly in live trading environments.
• Delivery of robust, scalable, and high-performance systems supporting live trading.
• Tangible improvements to research productivity, execution quality, and platform stability.
• Technical excellence and system ownership.