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- Tasks: Join us to challenge financial norms using cutting-edge machine learning techniques.
- Company: G-Research is a top-tier quantitative research firm based in London and Dallas.
- Benefits: Enjoy competitive pay, 35 days leave, free lunch, and a relaxed dress code.
- Why this job: Work in a vibrant culture that rewards innovative ideas and offers real-world impact.
- Qualifications: Post-graduate degree or commercial experience in machine learning; strong programming skills required.
- Other info: Collaborate with leading researchers and attend top conferences like NeurIPS and ICML.
The predicted salary is between 43200 - 72000 £ per year.
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
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Machine Learning Researcher employer: G-Research
Contact Detail:
G-Research Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Researcher
✨Tip Number 1
Familiarise yourself with the latest research in machine learning, especially topics like deep learning and reinforcement learning. Being able to discuss recent publications or breakthroughs during your interview will show your passion and commitment to the field.
✨Tip Number 2
Engage with the data science community by participating in online competitions, such as Kaggle. This not only sharpens your skills but also provides you with tangible achievements to discuss, which can set you apart from other candidates.
✨Tip Number 3
Brush up on your programming skills, particularly in Python and libraries like Scikit-Learn and NumPy. Being proficient in these tools is crucial for the role, and demonstrating your coding abilities in practical scenarios can make a strong impression.
✨Tip Number 4
Network with current employees or alumni from G-Research through platforms like LinkedIn. Gaining insights into their experiences and the company culture can help you tailor your approach and demonstrate your genuine interest in joining their team.
We think you need these skills to ace Machine Learning Researcher
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, particularly any work with deep learning, reinforcement learning, or data science competitions like Kaggle. Emphasise your programming skills in Python and familiarity with libraries such as Scikit-Learn and Pandas.
Craft a Strong Cover Letter: In your cover letter, express your passion for tackling complex problems in finance using machine learning. Mention specific projects or research that align with G-Research's focus on innovative ML techniques and your ability to develop novel algorithms.
Showcase Publications: If you have published work in top conferences like NeurIPS or ICML, make sure to include this in your application. Highlighting your contributions to the field will demonstrate your expertise and commitment to advancing machine learning research.
Demonstrate Problem-Solving Skills: Provide examples of how you've approached challenging problems in your previous roles or projects. Discuss your reasoning skills and mathematical abilities, especially in developing custom models when off-the-shelf methods were insufficient.
How to prepare for a job interview at G-Research
✨Showcase Your Technical Skills
Be prepared to discuss your experience with machine learning algorithms and programming languages, particularly Python. Highlight any projects or competitions you've participated in, such as Kaggle, to demonstrate your practical knowledge.
✨Understand the Company’s Focus
Research G-Research's approach to finance and their use of machine learning. Familiarise yourself with their recent publications and the techniques they employ, as this will show your genuine interest and help you align your answers with their goals.
✨Prepare for Problem-Solving Questions
Expect to tackle complex problems during the interview. Practice explaining your thought process clearly and logically, especially when discussing how you would develop models for unique datasets that may not fit standard methods.
✨Engage with Their Research Community
Demonstrate your enthusiasm for collaboration by discussing how you stay updated with the latest research in machine learning. Mention any conferences you've attended or papers you've read, as this aligns with their vibrant research culture.
