At a Glance
- Tasks: Research and apply Machine Learning techniques to identify trading opportunities.
- Company: Global quantitative hedge fund with a focus on systematic trading.
- Benefits: Competitive salary, discretionary bonuses, and opportunities for professional growth.
- Other info: Collaborative global environment with excellent career advancement potential.
- Why this job: Join a dynamic team and make an impact in the finance world using cutting-edge technology.
- Qualifications: Strong background in numerical fields and coding proficiency, preferably in Python.
The predicted salary is between 150000 - 200000 € per year.
£150,000-200,000 GBP
Discretionary end of year bonus
Onsite WORKING
Location: Central London, Greater London - United Kingdom
Type: Permanent
My client is a quantitative hedge fund with offices globally, focusing on systematic trading. Their Quant Researchers develop and monitor strategies covering all liquid markets, including HFT/arbitrage, statistical arbitrage, CTA, Macro and event-driven models. The firm has a mandate for Quantitative Researchers who are specialised in Machine Learning, Deep Learning, Reinforcement Learning, NLP, or Computer Vision.
Successful applicants will apply these techniques to analyse datasets and identify trading opportunities, and develop them into monetisable strategies in collaboration with other researchers, developers, and traders.
The Role:
- Researching and applying Machine Learning and other Data Science techniques to analyse datasets and identify alphas.
- You will work closely with other researchers, developers and traders on the development and implementation of these strategies, and monitor their performance over time.
- Quantitative Researchers collaborate with each other globally. You will share ideas and work on tools for others to use across the firm, expanding the business and building your own skills.
Requirements:
- An academic background with degrees covering numerical fields of study, such as Computer Science, Mathematics, and Quantitative Finance, PhD level degrees are preferred but not required.
- Experience/knowledge of finance from academic studies, internships or professional experience.
- Coding proficiency in at least one language, successful candidates are typically expert users of Python, and proficient with data science libraries.
Machine Learning Quant Researcher in London employer: ANSON MCCADE
As a leading quantitative hedge fund located in the heart of Central London, we pride ourselves on fostering a dynamic and collaborative work culture that encourages innovation and professional growth. Our Machine Learning Quant Researchers benefit from competitive salaries, discretionary bonuses, and the opportunity to work alongside top-tier talent in a fast-paced environment, all while contributing to cutting-edge trading strategies that shape the future of finance.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Quant Researcher in London
✨Tip Number 1
Network like a pro! Reach out to professionals in the industry through LinkedIn or attend relevant meetups. Building connections can lead to insider info on job openings and even referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects. Whether it's a GitHub repo or a personal website, having tangible examples of your work can really impress potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the latest trends in quantitative research. Practice common interview questions and be ready to discuss your past projects in detail.
✨Tip Number 4
Don’t forget to apply through our website! We have loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to get noticed by our hiring team directly.
We think you need these skills to ace Machine Learning Quant Researcher in London
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 achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about the role and how your background makes you a perfect fit. We love seeing enthusiasm and a clear understanding of what we do at StudySmarter.
Showcase Your Coding Skills:Since coding proficiency is key for this role, make sure to mention your experience with Python and any data science libraries you’ve used. If you have any personal projects or contributions to open-source, include those too – we love a proactive approach!
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at ANSON MCCADE
✨Know Your Algorithms
Brush up on your machine learning algorithms and their applications in finance. Be ready to discuss how you’ve used techniques like reinforcement learning or NLP in past projects, as this will show your practical understanding of the concepts.
✨Showcase Your Coding Skills
Since coding proficiency is key, prepare to demonstrate your skills in Python. You might be asked to solve a problem on the spot, so practice coding challenges and be familiar with data science libraries like Pandas and NumPy.
✨Understand the Market
Familiarise yourself with current trends in quantitative trading and systematic strategies. Being able to discuss recent market movements or successful trading strategies will impress your interviewers and show your passion for the field.
✨Collaborative Mindset
Emphasise your ability to work in teams. Since collaboration with researchers, developers, and traders is crucial, share examples of how you’ve successfully worked in teams to develop strategies or solve complex problems.
