EKA Finance is working with a highly regarded quantitative investment firm looking to add researchers to its systematic investment team.

The opportunity is suitable for both exceptional recent graduates / PhDs and experienced quantitative researchers with up to several years of relevant industry experience .

The team develops systematic investment strategies across liquid global markets. Researchers are given significant scope to develop original ideas, test hypotheses rigorously and work closely with experienced investors to turn research into implementable strategies.

The role

You will:

1. Research new systematic investment ideas across liquid markets.
2. Form and test hypotheses using large financial and alternative datasets.
3. Develop statistical, econometric and machine-learning models where appropriate.
4. Analyse market behaviour, risk factors and relationships across assets.
5. Build robust research and backtesting frameworks.
6. Evaluate signals for robustness, stability and economic rationale.
7. Work with senior researchers and portfolio managers to develop ideas from initial research through to implementation.
8. Contribute to a collaborative research environment where intellectual curiosity and independent thinking are highly valued.

Background:-

We are interested in candidates with a strong quantitative background in areas such as:

1. Mathematics
2. Statistics
3. Physics
4. Computer Science
5. Engineering
6. Econometrics
7. Quantitative Finance

We are open to candidates from both industry and academia .

Relevant professional experience may include quantitative research, systematic trading, signal research, portfolio research, machine learning, statistical modelling, time-series analysis, optimisation or other research-intensive quantitative work.

Prior experience in systematic investing is highly relevant, but not essential for exceptional candidates coming directly from academia .

You should have:

1. Strong quantitative and analytical ability.
2. Experience conducting rigorous empirical research.
3. Good programming skills, ideally Python or a similar research language.
4. A strong understanding of statistics, probability and modelling.
5. The ability to form independent hypotheses rather than simply apply existing models.
6. Genuine interest in financial markets and systematic investing.

The firm offers the opportunity to work alongside highly experienced quantitative investors in an environment with a strong emphasis on research quality, mentorship and long-term development .