Elite Quant Researcher -Global Systematic Investment Firm/ London/ USA - #2116190

We are working with a highly regarded quantitative investment firm looking to hire exceptional Quantitative Researchers across its London and US offices.

The firm uses advanced mathematics, statistics, machine learning and large-scale data analysis to identify investment and trading opportunities across global financial markets.

Researchers work closely with experienced quantitative portfolio managers, engineers and fellow researchers. The environment is highly collaborative and provides exposure to a broad range of datasets, research techniques, markets and asset classes.

This opportunity is aimed at candidates with genuinely outstanding mathematical and research ability. A PhD qualification by itself will not be sufficient.

The Role

You will research and develop mathematical and statistical models used within systematic investment strategies.

Your work will cover the full research process, from investigating datasets and developing hypotheses through to testing models, implementing successful signals and supporting their use in live trading.

You will receive direct guidance from senior quantitative portfolio managers and engineers with extensive experience across global markets.

Responsibilities

1. Analyse and evaluate large, complex financial and alternative datasets.
2. Formulate original research hypotheses and determine how they can be tested rigorously.
3. Research, develop and implement quantitative trading signals and predictive models.
4. Investigate established and emerging techniques in machine learning, statistics and data science.
5. Evaluate models using robust in-sample and out-of-sample research methodologies.
6. Identify and control for overfitting, data leakage, selection bias and false discoveries.
7. Assess the statistical robustness, economic rationale and commercial relevance of research findings.
8. Develop and maintain modelling, data and research infrastructure.
9. Convert successful research ideas into reliable production implementations.
10. Monitor live models and investigate changes in their behaviour or performance.
11. Support ongoing production trading operations.
12. Collaborate closely with quantitative portfolio managers, engineers and other researchers.
13. Contribute research ideas across different markets, datasets and asset classes.

Candidate Profile

We are looking for candidates with exceptional quantitative reasoning, intellectual curiosity and original research ability.

Applicants will typically have:

1. A PhD, or equivalent advanced research experience, involving intensive mathematics, statistics, computer science, machine learning, physics, engineering or another highly quantitative discipline.
2. A consistently outstanding academic record in mathematically rigorous subjects.
3. Research experience requiring substantial mathematical, statistical or computational depth.
4. Evidence of original problem-solving rather than the routine application of established models.
5. Strong knowledge of probability, statistics, optimisation, linear algebra, machine learning or numerical methods.
6. Excellent programming ability, ideally using Python.
7. Experience working with large, noisy, high-dimensional or otherwise complex datasets.
8. The ability to design careful experiments and draw reliable conclusions from uncertain data.
9. The ability to explain complex research clearly and defend the assumptions behind it.
10. A collaborative working style and willingness to engage closely with researchers, engineers and investors.
11. The flexibility to learn unfamiliar markets, modelling techniques and asset classes.

Evidence of Exceptional Ability

Holding a PhD alone will not automatically qualify a candidate for this position.

Strong applicants should be able to demonstrate clear evidence of exceptional mathematical, research or computational ability through one or more of the following:

1. Outstanding academic results in highly quantitative subjects.
2. Departmental prizes, scholarships, academic distinctions or competitive research awards.
3. A thesis containing substantial original mathematical, statistical or computational research.
4. High-quality publications in respected peer-reviewed journals or conferences.
5. Mathematics Olympiad, Putnam, ICPC or comparable mathematics or programming competition experience.
6. Significant independent research projects demonstrating creativity and technical depth.
7. The development of new mathematical, statistical or machine-learning methods.
8. Research involving difficult, noisy or previously unexplored datasets.
9. Evidence of solving technically challenging problems from first principles.
10. Experience translating complex research into reliable software or production systems.

Candidates should be prepared to explain the originality, difficulty and significance of their academic or professional research.

We are unlikely to progress applicants whose principal qualification is simply the completion of a PhD without clear evidence of mathematical excellence, research originality or outstanding technical ability.

Desirable Experience

The following experience would be helpful but is not essential:

1. Quantitative research within financial markets.
2. Systematic trading or investment research.
3. Developing predictive signals or statistical models.
4. Financial, alternative or market data.
5. Time-series or cross-sectional modelling.
6. Portfolio construction and optimisation.
7. Rigorous backtesting and out-of-sample validation.
8. Machine learning applied to noisy real-world datasets.
9. Python-based research environments.
10. C++, SQL or production-grade data infrastructure.
11. Taking a research project from initial idea through to production.

Previous hedge-fund experience, a portable trading strategy and a live track record are not required.

The firm is primarily interested in exceptional research potential, mathematical ability and the capacity to become a high-quality quantitative investor.

The Opportunity

This position offers: