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For Companies At a Glance
- Tasks: Conduct research, create predictive models, and implement algorithms for trading solutions.
- Company: Global leading quantitative trading firm with a focus on innovation.
- Benefits: Competitive pay, strong benefits, and opportunities for professional growth.
- Why this job: Join a dynamic team and contribute to cutting-edge trading strategies in global markets.
- Qualifications: Advanced degree in a quantitative field and strong programming skills in Python.
- Other info: Collaborative environment with opportunities in major financial hubs like London and New York.
The predicted salary is between 36000 - 60000 ÂŁ per year.
We’re partnering with a prominent global quantitative trading firm focused on market‑making and systematic strategies across various asset classes. The team applies advanced quantitative methods and technology to develop effective trading solutions in dynamic markets.
This is a hands‑on research position suited to strong performers with experience in generating alpha through data‑driven analysis and modelling.
What You’ll Work On
- Perform detailed research and statistical analysis and create predictive models for trading signals.
- Work with large‑scale datasets to discover and validate statistical patterns in markets.
- Develop and refine valuation approaches, construct and enhance mathematical and machine learning models.
- Implement complex algorithms into efficient, production‑grade code.
- Conduct rigorous backtesting and assist with deploying models into live trading systems.
- Collaborate with traders, engineers, and fellow researchers to improve systematic strategies across multiple asset classes.
What We’re Looking For
- Advanced degree (Master’s or PhD preferred; strong Bachelor’s considered) in Mathematics, Statistics, Physics, Computer Science, Engineering, or a related quantitative field.
- Solid expertise in probability, statistics, and quantitative techniques.
- Practical experience with machine learning and deep learning applied to financial or time‑series data.
- Proven success as a quantitative researcher or analyst, preferably in buy‑side quantitative trading or hedge funds (sell‑side experience also relevant).
- Strong programming skills in Python (required), with familiarity in analytical tools and/or compiled languages.
- Experience handling large datasets and developing reliable models in a data‑heavy research setting.
- Strong problem‑solving skills, with a track record of independent research and delivering tangible results.
- Clear communication abilities to explain complex concepts effectively.
Preferred
- Background in building automated trading strategies or signals in equities, fixed income, commodities, FX, or other asset classes.
- Exposure to unconventional data sources for alpha generation.
- Experience turning mathematical models into scalable production code for trading systems.
Why Join
- Contribute to advanced quantitative trading strategies operating in global markets.
- Work in a collaborative, merit‑based environment with talented researchers and engineers.
- Enjoy competitive compensation, strong benefits, and potential for professional development.
- Be part of a firm focused on innovation and ongoing improvement in quantitative finance.
- Opportunities available in key financial centers (London, New York, and Asia).
If you’re a skilled quant with solid ML experience and a demonstrated ability to generate alpha, we’d like to connect! Apply now to schedule a confidential chat with one of our team.
Quant Researcher/Quant Analyst @ Global Leading Firm employer: HUG
Contact Detail:
HUG Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quant Researcher/Quant Analyst @ Global Leading Firm
✨Tip Number 1
Network like a pro! Reach out to current or former employees of the firm on LinkedIn. A friendly chat can give us insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Prepare for those tricky technical interviews! Brush up on your quantitative skills and be ready to discuss your past projects. We want to see how you think and solve problems, so practice explaining your thought process clearly.
✨Tip Number 3
Show off your coding chops! If you’ve got a GitHub or similar portfolio, make sure it’s up to date with your best work. We love seeing practical examples of your programming skills, especially in Python.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team.
We think you need these skills to ace Quant Researcher/Quant Analyst @ Global Leading Firm
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of Quant Researcher/Analyst. Highlight your experience with statistical analysis, machine learning, and any relevant projects that showcase your skills in handling large datasets.
Craft a Compelling Cover Letter: Your cover letter should tell us why you're the perfect fit for this position. Share specific examples of how you've generated alpha through data-driven analysis and how your background aligns with our needs.
Showcase Your Programming Skills: Since strong programming skills in Python are a must, be sure to mention any relevant projects or experiences where you've implemented complex algorithms or developed production-grade code.
Apply Through Our Website: We encourage you to apply directly through our website. This way, we can easily track your application and ensure it gets the attention it deserves. Plus, it shows us you're serious about joining our team!
How to prepare for a job interview at HUG
✨Know Your Numbers
Brush up on your statistics and quantitative techniques. Be ready to discuss specific models you've worked on and the results they produced. This is your chance to showcase your expertise in probability and data analysis.
✨Showcase Your Coding Skills
Since strong programming skills in Python are a must, prepare to demonstrate your coding abilities. Bring examples of your work, especially any algorithms or models you've implemented. Being able to explain your code clearly will impress the interviewers.
✨Prepare for Technical Questions
Expect questions that dive deep into machine learning and statistical methods. Practice explaining complex concepts in simple terms, as clear communication is key. Think about how you can relate your answers back to real-world trading scenarios.
✨Collaborative Mindset
This role involves working closely with traders and engineers, so be prepared to discuss your teamwork experiences. Highlight instances where collaboration led to successful outcomes, and show that you're open to feedback and new ideas.
