We tackle the most complex problems in quantitative finance from our London HQ, uniting world‑class researchers and engineers in an environment that values deep exploration and methodical execution – because the best ideas take time to evolve. Together we’re building a world‑class platform to amplify our teams’ most powerful ideas. Join a research team where curiosity meets scale. You’ll investigate foundational questions, uncover market insights and push the boundaries of what’s possible – all with the support of near‑limitless compute and world‑class peers.
The role – Our researchers aim to disprove the efficient market hypothesis every day, harnessing massive compute power and state‑of‑the‑art ML techniques published in recent conferences or developed entirely in‑house. ML is integral to develop successful investment management strategies and is a core driver of our overall performance and success. Our ML practitioners have huge amounts of clean data and near‑infinite compute at their fingertips; they’re incentivised to explore the cutting‑edge and find the 1% difference. Unlike pure problems, our researchers get near instantaneous feedback in the form of absolute numbers where success is highly measurable and has a direct impact on the business. As a team we read the latest publications in the field, discuss them within our vibrant, collaborative research community, and attend leading conferences worldwide, such as NeurIPS and ICML.
In this research role you will develop and test your ideas with real‑world data in an academic environment.
Qualifications
- Either a post‑graduate degree in machine learning or a related discipline, or commercial experience developing novel machine learning algorithms.
- Exceptional candidates with a proven record of success in online data science competitions, such as Kaggle.
- Experience in deep learning, reinforcement learning, non‑convex optimisation, Bayesian non‑parametrics, NLP or approximate inference.
- Excellent reasoning skills and mathematical ability.
- Strong programming skills and experience working with Python, Scikit‑Learn, SciPy, NumPy, Pandas and Jupyter Notebooks; experience with object‑oriented programming is beneficial.
- Publications at top conferences, such as NeurIPS, ICML or ICLR, are highly desirable.
Why should you apply?
- Highly competitive compensation plus annual discretionary bonus.
- Lunch provided (via Just Eat for Business) and dedicated barista bar.
- 35 days’ annual leave.
- 9% company pension contributions.
- Informal dress code and excellent work/life balance.
- Comprehensive healthcare and life assurance.
- Cycle‑to‑work scheme.
- Monthly company events.
G‑Research is committed to cultivating and preserving an inclusive work environment. We want to ensure that applicants receive a recruitment experience that enables them to perform at their best. If you have a disability or special need that requires accommodation please let us know in the relevant section.
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