At a Glance
- Tasks: Develop cutting-edge trading strategies using machine learning and collaborate with top experts.
- Company: Globally leading quant hedge fund with a strong track record in systematic equities.
- Benefits: Competitive salary, market-leading bonus, and a fast-paced, collaborative environment.
- Other info: Join a dynamic team with opportunities for significant career growth.
- Why this job: Make a real impact in finance while working with state-of-the-art technology.
- Qualifications: Experience in machine learning, programming skills, and a degree in a quantitative field.
The predicted salary is between 60000 - 80000 € per year.
Competitive Base Salary + Market Leading Bonus
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.
- Hands on experience with PyTorch, TensorFlow, or similar packages.
HIGHLY VALUED RELEVANT EXPERIENCE
Prior research in applying machine learning models on intraday securities return prediction.
Machine Learning Systematic Equities Quantitative Researcher in London employer: ANSON MCCADE
Our client is an exceptional employer, offering a dynamic and collaborative work culture in the heart of Central London. With a focus on innovation and employee growth, they provide competitive salaries and market-leading bonuses, alongside opportunities to work with cutting-edge machine learning techniques in a fast-paced environment where your contributions are valued and impactful.
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 machine learning techniques and be ready to discuss your past projects. We recommend practising common interview questions and even doing mock interviews with friends or mentors.
✨Tip Number 3
Showcase your skills! Create a portfolio of your work, especially any projects involving systematic trading strategies or machine learning models. This will give potential employers a clear view of what you can bring to the table.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, applying directly can sometimes give you an edge over other candidates.
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, especially in Python or C++. We want to see how your background aligns with our needs!
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 skills can contribute to our team. Be specific about your experience with systematic trading strategies and machine learning.
Showcase Relevant Projects:If you've worked on any projects involving machine learning models or quantitative trading, make sure to include them in your application. We love seeing real-world applications of your skills, so don’t hold back on the details!
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at ANSON MCCADE
✨Know Your ML Techniques
Make sure you brush up on the latest machine learning techniques, especially those 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, GBMs, or DNNs.
✨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 on the spot, so practice common algorithms and data structures beforehand.
✨Research the Company and Team
Familiarise yourself with the hedge fund's history, its trading strategies, and the team’s approach to quantitative research. This will not only help you answer questions more effectively but also show your genuine interest in the role and the company.
✨Prepare for Technical Questions
Expect technical questions that dive deep into your quantitative research experience. Be ready to discuss your past projects, particularly those involving intraday securities return prediction, and how you approached data gathering, analysis, and model implementation.
