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For Companies At a Glance
- Tasks: Develop cutting-edge trading strategies using machine learning and data analysis.
- Company: Globally leading quant hedge fund with a strong track record.
- Benefits: Competitive salary, market-leading bonus, and a collaborative work environment.
- Other info: Join a dynamic team with opportunities for growth and innovation.
- Why this job: Make a real impact in a fast-paced role with visible results.
- Qualifications: Experience in machine learning and strong programming skills required.
The predicted salary is between 80000 - 100000 £ per year.
Location: Central London, Greater London - United Kingdom
Type: Permanent
TEAM OVERVIEW
Our client is a globally leading quant hedge fund, and a quantitative research and trading team with a strong track record in systematic equities. The founding members have approximately 70 years quantitative trading experience between them, with backgrounds from the senior ranks at top tier institutions. Having established the core infrastructure, trading processes and delivered performance, they are now looking to aggressively expand across multiple areas of the business. For the right individual they offer a highly rewarding front office role in a fast paced and collaborative environment, where each individual's impact can be clearly seen.
PRINCIPAL RESPONSIBILITIES
- Work alongside the Portfolio Manager on developing systematic trading strategies
- Primary focus on idea generation, data gathering and research/analysis, model implementation, and backtesting
- Work on state of the art machine learning techniques to extract alphas for statistical arbitrage strategies
REQUIRED TECHNICAL SKILLS
- Demonstrable experience in the latest ML techniques in a production setting
- Strong programming skills in any object-oriented language such as Python and C++
- Bachelors, Masters, or PhD in a quantitative subject such as Computer Science, Applied Mathematics, Statistics, or related field from a top ranked university
PREFERRED EXPERIENCE
- 2-5 years of experience working in a quantitative research/trading capacity with a focus on mid-to-high frequency equities and/or futures strategies
- Experience with signals that use non-linear machine learning models, such as SVMs, GBMs, or DNNs.
Machine Learning Systematic Equities Quantitative Researcher in London employer: eFinancialCareers
Contact Detail:
eFinancialCareers Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Systematic Equities Quantitative Researcher in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect on LinkedIn. We all know that sometimes it’s not just what you know, but who you know that can land you that dream role.
✨Tip Number 2
Prepare for those interviews! Brush up on your technical skills and be ready to discuss your past projects. We recommend practising common interview questions and even doing mock interviews with friends or mentors to boost your confidence.
✨Tip Number 3
Showcase your passion for machine learning! Bring examples of your work, whether it's a project, a paper, or even a GitHub repo. We want to see your enthusiasm and how you’ve applied your skills in real-world scenarios.
✨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 take the initiative to engage directly with us.
We think you need these skills to ace Machine Learning Systematic Equities 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 Systematic Equities Quantitative Researcher. Highlight your experience with ML techniques and programming skills, as these are key for us.
Craft a Compelling Cover Letter: Your cover letter should tell us why you're the perfect fit for this role. Share specific examples of your past work in quantitative research and how it aligns with our team's goals.
Showcase Your Projects: If you've worked on any relevant projects, make sure to include them in your application. We love seeing practical applications of your skills, especially in systematic trading strategies.
Apply Through Our Website: Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity.
How to prepare for a job interview at eFinancialCareers
✨Know Your ML Techniques
Make sure you brush up on the latest machine learning techniques relevant to systematic trading. Be ready to discuss how you've applied these in a production setting, and have examples at hand that showcase your experience with models like SVMs or GBMs.
✨Showcase Your Programming Skills
Since strong programming skills are a must, be prepared to demonstrate your proficiency in languages like Python or C++. You might even be asked to solve a coding problem during the interview, so practice common algorithms and data structures beforehand.
✨Understand the Business
Research the hedge fund's trading strategies and performance history. Understanding their approach to systematic equities will help you tailor your responses and show that you're genuinely interested in contributing to their success.
✨Prepare for Technical Questions
Expect technical questions that dive deep into quantitative research and trading concepts. Brush up on your statistics and quantitative analysis skills, and be ready to explain your thought process when developing trading strategies or conducting backtests.