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- Tasks: Conduct cutting-edge research in machine learning to model market behaviour and generate alpha.
- Company: Join a leading global hedge fund with over $35B AUM.
- Benefits: Work in a data-driven environment with direct impact on live investment strategies.
- Why this job: Transform academic research into real-world trading impact in a collaborative team.
- Qualifications: PhD or Master's in a quantitative field; strong ML programming skills required.
- Other info: Unique opportunity for career growth in finance and technology.
The predicted salary is between 36000 - 60000 £ per year.
A leading global hedge fund with over $35B AUM is seeking a Quantitative Machine Learning Researcher to join its growing systematic research group. The team applies advanced ML and statistical techniques to develop predictive models, identify alpha signals, and optimize portfolio construction across global markets. This is a unique opportunity for a top-tier researcher with strong academic credentials and hands-on technical skills to work in a world-class, data-driven environment with direct impact on live investment strategies.
Key Responsibilities:
- Conduct research into machine learning and statistical methods to model market behaviour and generate alpha.
- Design and test predictive features using large, diverse, and noisy datasets across equities, futures, and macro products.
- Contribute to signal validation, model explainability, and robustness testing for production-ready strategies.
- Collaborate with portfolio managers, engineers, and data scientists to integrate models into live trading frameworks.
- Explore new data sources and ML techniques to expand signal coverage and performance.
Core Skills & Experience:
- PhD (or Master’s with 1–2 years of experience) in a quantitative discipline such as Machine Learning, Computer Science, Statistics, Physics, Mathematics, or Engineering.
- Degree from a top 20 global university (e.g., Oxford, Cambridge, MIT, Stanford, Harvard, Princeton, ETH, Imperial, etc.).
- Strong background in machine learning, deep learning, or reinforcement learning.
- Hands-on programming experience in Python (PyTorch, TensorFlow, NumPy, Pandas, Scikit-learn).
- Solid understanding of statistical modeling, time-series analysis, and data preprocessing.
- Familiarity with financial markets, quantitative trading, or asset pricing concepts preferred but not required.
- Self-directed researcher with excellent problem-solving skills and a strong desire to work in a high-performance team.
This is a rare opportunity to transition cutting-edge research into live trading impact — combining academic rigor with real-world scalability in a collaborative, world-class environment.
Machine Learning Researcher employer: HWTS Global
Contact Detail:
HWTS Global Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Researcher
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, conferences, or webinars related to machine learning and finance. You never know who might have a lead on your dream job or can introduce you to someone at that hedge fund.
✨Show Off Your Skills
Create a portfolio showcasing your projects and research. Use GitHub to share your code and demonstrate your programming prowess in Python. This is your chance to shine and show potential employers what you can bring to the table!
✨Ace the Interview
Prepare for technical interviews by brushing up on your machine learning concepts and coding skills. Practice explaining your thought process clearly and concisely. Remember, they want to see how you approach problems, so don’t hold back!
✨Apply Through Our Website
Don’t forget to apply directly through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Machine Learning Researcher
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to highlight your experience in machine learning and quantitative research. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or research.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about this role and how your background makes you a perfect fit. We love seeing enthusiasm and a clear understanding of our work.
Showcase Your Technical Skills: Don’t forget to mention your programming skills, especially in Python and any libraries like PyTorch or TensorFlow. We’re looking for hands-on experience, so include specific examples of projects where you’ve applied these skills.
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people!
How to prepare for a job interview at HWTS Global
✨Know Your Stuff
Make sure you brush up on your machine learning concepts and statistical methods. Be ready to discuss your research and how it applies to market behaviour. They’ll want to see that you can translate complex ideas into practical applications.
✨Showcase Your Skills
Prepare to demonstrate your programming prowess, especially in Python. Have examples ready of projects where you've used libraries like PyTorch or TensorFlow. Being able to talk through your code and the thought process behind it will impress them.
✨Understand the Financial Landscape
Even if you’re not a finance whiz, having a basic understanding of financial markets and quantitative trading will set you apart. Familiarise yourself with key concepts and be prepared to discuss how your work could impact investment strategies.
✨Be Collaborative
This role involves working closely with portfolio managers and data scientists, so highlight your teamwork skills. Share examples of how you’ve successfully collaborated on projects in the past, and express your enthusiasm for being part of a high-performance team.
