Helix Junior Quantitative Developer

iSAM is an innovative, financial technology firm specialising in quantitative trading, comprised of iSAM Funds and iSAM Securities.

iSAM Securities regulated by the FCA, SFC, and CIMA registered, is a leading algorithmic trading firm and trusted electronic market maker, providing liquidity, technology and prime services to institutional clients and trading venues globally. The firm offers full-service prime brokerage and execution via its cutting-edge proprietary technology, as well as market leading analytics, cleared through the group’s bank Prime Brokers.

iSAM Funds is an alternative asset manager specialising in systematic investing. Each strategy is unique, provides a specialist quantitative approach and is designed to deliver highly diversifying absolute returns for institutional portfolios.

About the Role:

iSAM Helix is an Equities Statistical Arbitrage (StatArb) business line within iSAM Funds, which trades 24/6 globally. iSAM Helix has been live since 2021 and continues to evolve rapidly as part of an ambitious roadmap focused on expanding strategy breadth and capacity. Helix consists of four groups: Research, Quantitative Development, Technology and Data. The project is highly collaborative; the team are looking for a Quantitative Developer capable of working on all aspects of the trading platform - research, development, and live trading platforms. Technology is a front-line function within Helix, playing a critical role in systematic trading. Both the research platform and the production trading system are built on top of custom implementation of high-performance python graph (DAG). The same graph framework is being used across the whole environment - research and back testing, live trading, analytics, risk, position keeping and P&L.

Responsibilities:

The opportunity would involve tackling complex problems in which you’d be a key part

of team working on a large breadth of challenges, including the following:

• Develop and support a complex quantitative StatArb strategies involving large-

  scale data processing, sophisticated statistical modelling, portfolio construction

  and highly optimised execution.

• Build and maintain systems handling highly diversified equity portfolios.
• Monitoring transaction costs and behaviour of a high turnover strategy.
• Process and analyse 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).

Qualifications:

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

bank, hedge fund and associated firms)

• Degree in Mathematics or Physics preferred; other STEM subjects such as

  Computer Science will also be considered.

• Python: Strong software developer with in-depth knowledge and experience.
• Numpy (including numba): in-depth knowledge is required.
• Strong knowledge of Unix systems (processes, memory, I/O).
• Deep understanding of statistical methods, numerical optimisation and equity

  market microstructure.

• Experience working with graph-based (DAG) data processing frameworks.

Personal Attributes:

• 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.

Key Outcomes: 

• 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.