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For Companies At a Glance
- Tasks: Join a dynamic team to develop and implement innovative trading strategies in FX markets.
- Company: A leading investment firm known for its rigorous research and systematic trading success.
- Benefits: Enjoy a competitive salary, bonuses, flexible working, and professional development opportunities.
- Why this job: Be part of a collaborative environment with ownership of projects and impactful work.
- Qualifications: 3+ years in quantitative research, strong Python skills, and an advanced degree in a quantitative field.
- Other info: Opportunity to engage in charity work and volunteer initiatives.
Job Description
Client
Research at this leading investment firm is key to continued success: based on rigorous and innovative research, they design and implement systematic, computer-driven trading strategies across multiple liquid asset classes.
Working within a small 'trading pod' as the right-hand person to the Portfolio Manager, you will do systematic macro trading within FX, running both intra-day strategies and building HFT strategies to run passively.
Role
They're looking to add an exceptional Quantitative Researcher with Python experience to their growing London team. You'll be tasked with discovering systematic anomalies in FX markets and identifying & evaluating new datasets. You'll also take on end-to-end development: from generating alpha ideas to strategy backtesting and optimization, through to production implementation.
With lots of project ownership and a collaborative start-up environment, this is a fantastic place to work.
Requirements:
- 3+ years' experience in a similar role (e.g. systematic alpha research in FX)
- Strong programming skills Python
- Advanced degree (MS or PhD) in Maths, or other quantitative fields, from a leading university
- Excellent grasp of foundations of applied statistics, linear algebra and time series models
Desirable:
- Experience developing short-term alpha signals
- Demonstrated proficiency with large, raw data sources
Benefits:
- Market-leading base + bonuses + generous benefits
- Meritocratic environment working with some of the smartest minds in industry
- Excellent professional development (tuition assistance)
- Plenty of opportunity to give back through volunteering & charity work
- Flexible hybrid working model
Whilst we carefully review all applications, to all jobs, due to the high volume of applications we receive it is not possible to respond to those who have not been successful.
Contact
If you feel you're suitable for this role, want to hear about similar positions, or would like help hiring similar developers for your company, please send your CV or get in touch.
Richard Allan
richard.allan@oxfordknight.co.uk
020 3137 9574
linkedin.com/in/richardallanok/
Python Quantitative Researcher - FX- Multi-Asset Class Systematic Trading employer: Oxford Knight
Contact Detail:
Oxford Knight Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Python Quantitative Researcher - FX- Multi-Asset Class Systematic Trading
✨Tip Number 1
Network with professionals in the quantitative finance space, especially those who work with FX and systematic trading. Attend industry conferences or meetups to connect with potential colleagues and learn about the latest trends and technologies.
✨Tip Number 2
Showcase your Python skills by contributing to open-source projects or creating your own portfolio of quantitative research projects. This will demonstrate your ability to apply your programming knowledge in real-world scenarios, which is crucial for this role.
✨Tip Number 3
Familiarise yourself with the latest research and methodologies in systematic trading and FX markets. Reading academic papers or following influential figures in the field can provide you with insights that may set you apart during interviews.
✨Tip Number 4
Prepare for technical interviews by practising problem-solving and coding challenges related to quantitative finance. Focus on topics like applied statistics, linear algebra, and time series models, as these are essential for the role.
We think you need these skills to ace Python Quantitative Researcher - FX- Multi-Asset Class Systematic Trading
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your Python programming skills and relevant experience in systematic alpha research, particularly in FX markets. Use specific examples to demonstrate your expertise in developing trading strategies.
Craft a Strong Cover Letter: Write a cover letter that showcases your passion for quantitative research and your understanding of the role. Mention your advanced degree and how it has equipped you with the necessary skills in applied statistics and linear algebra.
Highlight Relevant Projects: Include details about any projects where you've developed short-term alpha signals or worked with large datasets. This will show your practical experience and ability to contribute to the team immediately.
Proofread Your Application: Before submitting, carefully proofread your application materials for any errors or inconsistencies. A polished application reflects your attention to detail, which is crucial in quantitative research.
How to prepare for a job interview at Oxford Knight
✨Showcase Your Python Skills
Make sure to highlight your programming expertise in Python during the interview. Be prepared to discuss specific projects where you've used Python for quantitative research, especially in FX markets.
✨Demonstrate Your Analytical Thinking
Prepare to explain your approach to discovering systematic anomalies and how you evaluate new datasets. Use examples from your past experience to illustrate your analytical skills and thought process.
✨Understand the Trading Strategies
Familiarise yourself with various systematic trading strategies, particularly in FX and multi-asset classes. Being able to discuss these strategies intelligently will show your passion and understanding of the role.
✨Prepare for Technical Questions
Expect technical questions related to applied statistics, linear algebra, and time series models. Brush up on these topics and be ready to solve problems or explain concepts clearly during the interview.
