At a Glance
- Tasks: Design and build machine learning models to generate alpha in fast-paced trading environments.
- Company: Leading quantitative hedge fund at the forefront of high-frequency trading.
- Benefits: Competitive salary, dynamic work environment, and opportunities for professional growth.
- Other info: Collaborative culture with a focus on innovation and cutting-edge research.
- Why this job: Join a specialist team and make an impact in the exciting world of finance and technology.
- Qualifications: Advanced degree in a quantitative field and strong machine learning skills required.
The predicted salary is between 48000 - 72000 £ per year.
Company: A leading quantitative proprietary trading firm expanding into mid-frequency strategies across global equities, futures, and derivatives markets.
Location: London, United Kingdom.
Brief: The firm is a building a specialist, ML-driven alpha research team covering equity and futures markets.
Responsibilities:
- Design, build, and backtest machine learning models to generate alpha across HFT and mid-frequency settings.
- Work closely with infrastructure and execution teams to integrate models into production.
- Engage in data engineering and feature engineering: sourcing, cleaning, and transforming vast streams of market/alternative/microstructure/tick-level data.
- Develop strategies that adapt to market microstructure dynamics (e.g. order flow, market impact, latency arbitrage, predictive of short-term price movements).
- Conduct rigorous risk assessments and monitor/maintain live performance.
Requirements:
- Strong background in machine learning, deep learning, and statistical modelling (e.g., gradient boosting, neural networks, reinforcement learning).
- Proficiency in Python, C++ and high-performance computing environments are a bonus.
- Experience with financial time-series analysis, market microstructure, or electronic trading preferred.
Quantitative Researcher (Machine Learning) employer: Thurn Partners
As a leading quantitative hedge fund based in London, we pride ourselves on fostering a dynamic and innovative work culture that empowers our Quantitative Researchers to excel. Our commitment to employee growth is evident through continuous learning opportunities and collaboration with top-tier professionals in the field, all while working on cutting-edge machine learning projects that drive high-frequency trading strategies. Join us to be part of a forward-thinking team where your contributions directly impact our success in the fast-paced world of finance.
StudySmarter Expert Advice🤫
We think this is how you could land Quantitative Researcher (Machine Learning)
✨Tip Number 1
Network like a pro! Reach out to professionals in the quantitative finance space on LinkedIn or at industry events. We can’t stress enough how valuable personal connections can be in landing that dream role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning models and any relevant projects. This is your chance to demonstrate your expertise in Python, C++, and financial time-series analysis to potential employers.
✨Tip Number 3
Prepare for technical interviews by brushing up on your knowledge of machine learning algorithms and statistical modelling. We recommend doing mock interviews with friends or using online platforms to get comfortable with the format.
✨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, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Quantitative Researcher (Machine Learning)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the role of a Quantitative Researcher. Highlight your experience with machine learning, statistical modelling, and any relevant projects that showcase your skills in Python or C++. We want to see how you can bring value to our ML-driven HFT team!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about quantitative research and how your background aligns with our needs. Don’t forget to mention any specific experiences with financial time-series analysis or market microstructure that could set you apart.
Showcase Your Projects:If you've worked on any relevant projects, whether academic or personal, make sure to include them. Describe the challenges you faced, the solutions you implemented, and the outcomes. This will give us insight into your problem-solving skills and your ability to apply machine learning in real-world scenarios.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re proactive and keen to join our team!
How to prepare for a job interview at Thurn Partners
✨Know Your Models Inside Out
Make sure you can explain the machine learning models you've worked with in detail. Be ready to discuss how you designed, built, and backtested them, as well as any challenges you faced and how you overcame them.
✨Brush Up on Financial Concepts
Since this role involves high-frequency trading, it's crucial to understand market microstructure and financial time-series analysis. Familiarise yourself with concepts like order flow and latency arbitrage, so you can confidently discuss how your work impacts trading strategies.
✨Showcase Your Coding Skills
Be prepared to demonstrate your proficiency in Python and C++. You might be asked to solve a coding problem or explain your approach to integrating models into production, so practice coding under time constraints to simulate the interview environment.
✨Engage with Real-World Scenarios
Think about how your previous experiences relate to the responsibilities of the role. Prepare examples of how you've conducted risk assessments or monitored live performance, and be ready to discuss how you would adapt strategies to changing market conditions.
