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- Tasks: Design and enhance predictive models using cutting-edge financial data.
- Company: Top-tier systematic trading firm with a focus on innovation.
- Benefits: Competitive salary, full-time role, and opportunities for career advancement.
- Why this job: Make a real impact in the trading world with your quantitative skills.
- Qualifications: 4+ years in quantitative or ML roles; strong academic background required.
- Other info: Collaborative environment with experienced professionals and high-impact projects.
The predicted salary is between 43200 - 72000 £ per year.
A top-tier systematic trading firm is seeking exceptional Quantitative Researchers to advance and optimize proprietary trading strategies. You will collaborate with experienced researchers, engineers, and senior leadership, working on high-impact projects that shape the future of quantitative trading. As your career progresses, you will have the autonomy to lead independent research initiatives.
What You’ll Do:
- Design and improve predictive models using financial and alternative data
- Apply advanced ML and statistical methods to drive alpha generation
- Build and implement production-ready algorithms to capitalize on predictive insights
What They’re Looking For:
- 4+ years of experience in a quantitative or ML-focused role
- Strong academic background in Physics, Mathematics, Computer Science, ML, or a related technical discipline (BS, MS, PhD, or Postdoc)
- Demonstrated strength in problem-solving, modeling, and research methodology
- Proficient in Python, C++, Java, or R
- Experience in a trading environment a plus
Ready to leverage your quantitative skills and make an impact in the trading world? Apply now!
Machine Learning Quantitative Researcher in London employer: Alexander Chapman
Contact Detail:
Alexander Chapman Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Quantitative Researcher in London
✨Tip Number 1
Network like a pro! Reach out to professionals in the field through LinkedIn or industry events. A friendly message can go a long way in getting your foot in the door.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving predictive models and algorithms. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Don’t just apply; engage! When you find a job that excites you, reach out directly to the hiring manager or recruiter. A quick message expressing your enthusiasm can set you apart from the crowd.
✨Tip Number 4
Keep learning and adapting! Stay updated with the latest trends in machine learning and quantitative research. This shows you're passionate and committed, making you a more attractive candidate.
We think you need these skills to ace Machine Learning Quantitative Researcher in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of a Machine Learning Quantitative Researcher. Highlight your experience in quantitative roles and any relevant projects that showcase your skills in predictive modelling and algorithm development.
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 in Physics, Mathematics, or Computer Science makes you a perfect fit for the team.
Showcase Your Technical Skills: Don’t forget to mention your proficiency in programming languages like Python, C++, Java, or R. Include specific examples of how you've used these skills in previous roles to drive alpha generation or improve trading strategies.
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s quick and easy, and we can’t wait to see what you bring to the table!
How to prepare for a job interview at Alexander Chapman
✨Know Your Models Inside Out
Make sure you can discuss the predictive models you've designed and improved in detail. Be ready to explain your thought process, the data you used, and how you applied advanced ML methods to drive alpha generation.
✨Brush Up on Your Coding Skills
Since proficiency in Python, C++, Java, or R is crucial, practice coding problems related to algorithm implementation. You might be asked to write production-ready algorithms during the interview, so being sharp on your coding skills will definitely give you an edge.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in previous roles and how you tackled them. Highlight your research methodology and any innovative solutions you developed, as this will demonstrate your ability to think critically and creatively.
✨Understand the Trading Environment
If you have experience in a trading environment, be sure to bring it up! If not, do some research on how quantitative trading works and be prepared to discuss how your skills can contribute to optimising trading strategies.