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:
We have a Quantitative Research role available within the Quantitative Research function of iSAM Funds, for PhD graduates in their final year of their Econometrics or Economics course who have strong quantitative ability.
No prior industry experience is required—only intellectual curiosity, strong analytical ability, and a genuine eagerness to learn.
As an PhD graduate, you will be fully embedded within your team and contribute meaningfully to live research and trading initiatives. The role is research-focused and involves applying advanced statistical and mathematical techniques to develop and evaluate quantitative signals and strategies.
Responsibilities:
You will work as part of a collaborative research team, tackling complex and intellectually challenging problems. Responsibilities may include:
- Assisting in the research and development of systematic investment strategies
- Analysing large and complex financial datasets to identify signals, patterns, and risk characteristics
- Designing, implementing, and testing quantitative models using Python and relevant numerical and statistical libraries
- Documenting research methodologies and results, and presenting findings to senior researchers
- Collaborating closely with portfolio managers, quantitative researchers, and technologists
Qualifications
- PhD student in Econometrics or Economics with expected completion in 2026 or 2027
- Strong foundation in statistics and probability theory
- Strong programming skills in Python
- Experience handling large datasets
- A strong interest in financial markets and systematic trading
Personal Attributes
- Highly analytical, with a strong sense of ownership and accountability
- Enjoys tackling complex problems
- Collaborative and able to work effectively with researchers, technologists, and traders
- Clear and concise communicator, both verbally and in writing
- Comfortable working independently while knowing when to seek input from others
Key Objectives
- Developed a strong understanding of how quantitative research is conducted within a live trading environment
- Contributed tangible research that informs or enhances existing trading strategies or research directions
- Demonstrated the ability to translate complex mathematical or economic ideas into robust well-tested code
- Gained hands-on experience working with large-scale financial data and research infrastructure
- Built an understanding of the full research lifecycle, from idea generation and data analysis through to validation and presentation
- Established effective working relationships within their team, contributing proactively and collaboratively to shared objectives
- Strengthened problem-solving, communication, and technical skills in a fast-paced, intellectually rigorous setting