Do you want to tackle the biggest questions in finance with near infinite compute power at your fingertips?
G-Research is a leading quantitative research and technology firm, with offices in London and Dallas. We are proud to employ some of the best people in their field and to nurture their talent in a dynamic, flexible and highly stimulating culture where world-beating ideas are cultivated and rewarded.
This role is based in our new Soho Place office – opened in 2023 - in the heart of Central London and home to our Research Lab.
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
