Jobs at iSAM

Join iSAM Vector as a Quantitative Researcher to design, test and implement systematic trading signals across global markets. Responsibilities include signal research, backtesting, model refinement, dataset and tool development, portfolio construction support, and communicating results to technical and non-technical stakeholders.

Conduct portfolio and risk management for a new systematic multi-strategy trading platform. Build portfolio analytics and monitoring infrastructure, onboard quantitative strategies, improve platform operations, and support production on a rota. The role requires quantitative research experience, strong Python skills, expertise in statistics, probability, portfolio construction, and risk management, plus the ability to connect empirical research with practical investment implementation.

Develop and maintain scalable Python software for a systematic multi-strategy trading platform. Collaborate with quantitative researchers on strategy and portfolio development, ensure production code is robust and performant, improve platform capabilities, and support live production systems through a rota. The role spans the full trading technology lifecycle, including data, research, execution, monitoring, and platform reliability.

Supports fund operations for managed futures and quantitative funds by reviewing trading and cash reconciliations, performance estimates, corporate actions, reports, service providers, NAV calculations, cash management, settlements, and risk reporting. The role collaborates with investment managers, prime brokers, administrators, and internal teams to resolve discrepancies and ensure compliance with fund policies.

Monitor and optimize algorithmic trading strategies, ensuring operations remain within risk and compliance limits. Support global clients, manage communications during incidents, oversee internal connectivity systems, translate technical updates, and collaborate with sales and internal teams to convert client needs into strategy requirements. The role is on-site and involves weekend plus three weekday shifts.

Lead the development of exchange market-making and OTC inventory liquidation strategies across FX, precious metals, futures, and cryptocurrency markets. Research market microstructure, order-book behavior, liquidity, and adverse selection using high-frequency data. Build realistic simulations and backtests, deploy and monitor live strategies, improve performance and resilience, and establish research governance. The role will eventually define research direction and recruit, mentor, and lead a quantitative trading team.

PhD graduate embedded in a quantitative research team to develop, implement and test systematic investment strategies. Analyse large financial datasets, design statistical models in Python, document results, and present findings to senior researchers and portfolio managers.

The Helix Software Engineer will manage the ISAM Helix Trading System, improve trade execution, onboard new brokers, and enhance system architecture while supporting production.

12-week summer internship for PhD students to conduct quantitative research in trading and systematic investing. Work includes analysing large financial datasets, developing and backtesting quantitative models using Python and statistical libraries, validating strategies, maintaining research infrastructure, and presenting findings to senior researchers and trading teams.

Join the Helix StatArb team to develop, maintain, and support high-performance quantitative trading systems. Work on large-scale data processing, statistical modeling, portfolio construction, execution monitoring, and DAG-based concurrent data frameworks. Collaborate with researchers, own system components, and participate in live trading support and rota duties to ensure robust, scalable production trading infrastructure and improved execution quality.

Architect, build and operate low-latency distributed trading systems (market data, order routing, execution, risk, messaging). Drive technical direction, improve systems and engineering processes, reason about latency across network/hardware/OS/language layers, and deliver large cross-team efforts to meet demanding latency targets.