Quantitative Developer — DAG-Driven Trading & Research

iSAM Securities; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

iSAM Securities is seeking a Quantitative Developer to join iSAM Helix, an Equities Statistical Arbitrage business line trading globally. You will contribute to research, development and live trading, leveraging a graph-based DAG framework for high-performance data processing.

The ideal candidate has a strong Python background, expertise with NumPy/Numba and Unix, plus experience in statistical methods and DAG data processing.

Qualifications

• Degree in Mathematics or Physics preferred; other STEM subjects will be considered.
• Strong Python software development experience.
• In-depth knowledge of NumPy/Numba.
• Strong Unix systems knowledge (processes, memory, I/O).
• Experience with graph-based (DAG) data processing frameworks.

Responsibilities

• Develop and support quantitative StatArb strategies involving large-scale data, modelling, portfolio construction and execution.
• Build and maintain systems for diversified equity portfolios.
• Monitor transaction costs and behaviour of high-turnover strategies.
• Process and analyse large historical datasets for research and back-testing, plus real-time market data for live trading.
• Contribute to high-performance graph-based framework enabling concurrent data processing.
• Monitor execution quality, costs and market risks across regimes.
• Collaborate with researchers to enhance tooling and libraries.
• Own system components in a fast-paced, agile environment; work independently and with teams.
• Participate in live trading support, including interaction with orders and brokers (FCA certification required).

Skills

Python

NumPy/Numba

Unix

Statistical methods

Numerical optimisation

DAG frameworks

Education

Mathematics or Physics degree

STEM degree (e.g., Computer Science)

Tools

DAG framework

Job description

iSAM Securities is seeking a Quantitative Developer to join iSAM Helix, an Equities Statistical Arbitrage business line trading globally. You will contribute to research, development and live trading, leveraging a graph-based DAG framework for high-performance data processing.

The ideal candidate has a strong Python background, expertise with NumPy/Numba and Unix, plus experience in statistical methods and DAG data processing.