We tackle the most complex problems in quantitative finance, by bringing scientific clarity to financial complexity.
From our London HQ, we unite 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.
Take the next step in your career.
The role
Our researchers have a challenge: disproving the efficient market hypothesis every day. This requires them to harness massive compute power and to use state-of-the-art ML techniques – published in recent conferences or developed entirely in-house – as textbook methods won’t beat the competition.
ML is integral to develop successful investment management strategies; it is one of the core drivers of our overall performance and success. It has long been a key tool at G-Research and we count a range of ICML and NeurIPS published researchers among our people.
Our ML practitioners have huge amounts of (clean) data and near infinite compute at their fingertips, with which they’re incentivised to explore the cutting-edge and find the 1% of difference. And 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 and discuss them within the our vibrant, collaborative research community, and attend the leading conferences worldwide, such as NeurIPS and ICML.
In this research role you will be able to develop and test your ideas with real-world data in an academic environment.
Who are we looking for?
The ideal candidate will have:
- Either a post-graduate degree in machine learning or a related discipline, or commercial experience developing novel machine learning algorithms. We will also consider exceptional candidates with a proven record of success in online data science competitions, such as Kaggle
- Experience in one or more of deep learning, reinforcement learning, non-convex optimisation, Bayesian non-parametrics, NLP or approximate inference
- Excellent reasoning skills and mathematical ability are crucial: off-the-shelf methods don’t always work on our data so you will need to understand how to develop your own models
- Strong programming skills and experience working with Python, Scikit-Learn, SciPy, NumPy, Pandas and Jupyter Notebooks is desirable. Experience with object-oriented programming is beneficial
- Publications at top conferences, such as NeurIPS, ICML or ICLR, is 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
