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- Tasks: Lead the research lifecycle in machine learning for trading models.
- Company: Top capital markets firm in London with a flat structure.
- Benefits: Access to robust resources and impactful projects.
- Why this job: Make a real difference in options trading with your expertise.
- Qualifications: Masters or PhD in a quantitative field and strong Python skills.
- Other info: Exciting opportunity for career growth in a dynamic environment.
The predicted salary is between 43200 - 72000 £ per year.
A leading capital markets firm in London is seeking a Machine Learning Researcher to own the research lifecycle from hypothesis to deployment. Applicants should have a Masters or PhD in a quantitative field, strong expertise in machine learning, and proficiency in Python. The role offers the opportunity to develop models that have a direct impact on trading in options markets, supported by robust resources and a flat organizational structure.
ML Researcher — Quant Finance, End-to-End Impact (London) employer: Citadel Securities
Contact Detail:
Citadel Securities Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Researcher — Quant Finance, End-to-End Impact (London)
✨Tip Number 1
Network like a pro! Reach out to professionals in the quant finance space on LinkedIn or at industry events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those relevant to finance. This will give you an edge and demonstrate your hands-on experience.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python skills and understanding key ML concepts. Practice coding challenges and be ready to discuss your past projects in detail.
✨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!
We think you need these skills to ace ML Researcher — Quant Finance, End-to-End Impact (London)
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your expertise in machine learning and Python in your application. We want to see how your background aligns with the role, so don’t hold back on showcasing your projects or research!
Tailor Your Application: Customise your CV and cover letter to reflect the specific requirements of the ML Researcher position. We love seeing candidates who take the time to connect their experiences directly to what we’re looking for.
Be Clear and Concise: When writing your application, keep it straightforward and to the point. We appreciate clarity, so make sure your ideas flow well and are easy to understand. Avoid jargon unless it’s relevant!
Apply Through Our Website: We encourage you to submit your application through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Citadel Securities
✨Know Your Stuff
Make sure you brush up on your machine learning concepts and quantitative methods. Be ready to discuss your previous projects in detail, especially those that involved hypothesis testing and model deployment. This will show your depth of knowledge and practical experience.
✨Python Proficiency is Key
Since the role requires proficiency in Python, be prepared to demonstrate your coding skills. You might be asked to solve a problem on the spot or explain your thought process while coding. Practising common algorithms and data structures in Python can really help you shine.
✨Understand the Business Impact
Familiarise yourself with how machine learning models can influence trading strategies, particularly in options markets. Being able to articulate how your research can lead to tangible results will impress the interviewers and show that you’re not just technically skilled but also business-savvy.
✨Ask Insightful Questions
Prepare some thoughtful questions about the company’s approach to machine learning and their current projects. This shows your genuine interest in the role and helps you gauge if the company culture aligns with your values, especially in a flat organisational structure.
