At a Glance
- Tasks: Tackle big finance questions using cutting-edge machine learning techniques and massive compute power.
- Company: G-Research, a leading quantitative research and technology firm in London.
- Benefits: Competitive salary, annual bonus, 35 days leave, and comprehensive healthcare.
- Other info: Join a diverse team and enjoy excellent work/life balance with monthly company events.
- Why this job: Make a real impact in finance with your ML skills in a vibrant, collaborative environment.
- Qualifications: Post-graduate degree or commercial experience in machine learning; strong programming skills required.
The predicted salary is between 48000 - 72000 £ per year.
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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Machine Learning Researcher employer: Braunford LLP
G-Research is an exceptional employer that fosters a collaborative and innovative work culture, providing NLP interns with invaluable mentorship and hands-on experience in quantitative finance research. Located in London, interns benefit from access to cutting-edge technology and the opportunity to present their findings to senior management, paving the way for potential full-time roles post-graduation.
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We think you need these skills to ace Machine Learning Researcher
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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✨Brush Up on Your Statistics
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
