At a Glance
- Tasks: Design and manage data-driven trading models for global macroeconomic assets.
- Company: Join a leading firm focused on innovative quantitative research and trading strategies.
- Benefits: Enjoy a collaborative environment, competitive salary, and opportunities for professional growth.
- Other info: Ideal for those passionate about quantitative finance and eager to make a real-world impact.
- Why this job: Be part of a dynamic team that drives market strategies and impacts financial outcomes.
- Qualifications: PhD or MSc in a quantitative field; strong coding skills in Python/C# and SQL required.
The predicted salary is between 48000 - 72000 € per year.
Job Description
Role Overview:
The successful candidate will design, implement, and manage data-driven trading models across global macroeconomic assets. The position requires deep expertise in statistical and machine learning methodologies, alongside robust programming and data-handling capabilities. Applicants should bring a verifiable track record of high information ratio strategies deployed in real-market environments.
Key Responsibilities:
- Develop and deploy systematic trading models across macro asset classes, primarily using futures and foreign exchange instruments.
- Apply advanced quantitative methods—including time-series modeling, econometric analysis, and machine learning—to uncover alpha-generating signals.
- Conduct extensive backtesting and stress testing to evaluate performance robustness, execution latency, and risk-adjusted return characteristics.
- Collaborate within a research-driven environment to enhance alpha models, portfolio construction techniques, and signal processing infrastructure.
- Monitor and evolve deployed strategies to maintain performance amid shifting market regimes.
Ideal Background:
- Demonstrated experience in quantitative macro research or portfolio management, with a track record of alpha generation and strategy deployment.
- Exposure to short- and medium-term systematic trading styles, ideally within timeframes of hours to two weeks.
- Advanced academic training (PhD or MSc) in a quantitative discipline such as Financial Engineering, Applied Mathematics, Statistics, Computer Science, or Physics.
- Strong coding proficiency in Python and/or C#, with working knowledge of SQL for data manipulation and extraction.
- Eligible to work in the UK and able to operate effectively in a collaborative, research-intensive setting.
Senior Quantitative Researcher - Systematic Macro Strategies in London employer: Eka Finance
As a Senior Quantitative Researcher at our firm, you will thrive in a dynamic and collaborative environment that champions innovation and excellence in quantitative finance. We offer competitive remuneration, comprehensive benefits, and ample opportunities for professional development, ensuring that you can grow your expertise while contributing to cutting-edge trading strategies. Located in the heart of the financial district, our office provides a vibrant atmosphere that fosters creativity and teamwork, making it an ideal place for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Quantitative Researcher - Systematic Macro Strategies in London
✨Tip Number 1
Familiarise yourself with the latest trends in quantitative macro research. Stay updated on recent developments in machine learning and statistical methodologies, as these are crucial for the role. Engaging with relevant academic papers or industry reports can give you an edge.
✨Tip Number 2
Build a portfolio showcasing your previous work with trading models. Highlight any successful strategies you've developed, particularly those that demonstrate a high information ratio. This practical evidence of your skills can significantly bolster your candidacy.
✨Tip Number 3
Network with professionals in the quantitative finance space. Attend industry conferences, webinars, or local meetups to connect with others who share your interests. These connections can provide valuable insights and potentially lead to referrals.
✨Tip Number 4
Prepare to discuss your coding skills in Python and C# during interviews. Be ready to demonstrate your ability to manipulate data using SQL. Practising coding challenges or contributing to open-source projects can help you showcase your technical proficiency.
We think you need these skills to ace Senior Quantitative Researcher - Systematic Macro Strategies in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience in quantitative macro research and any relevant trading strategies you've developed. Emphasise your coding skills in Python and/or C#, as well as your academic qualifications.
Craft a Strong Cover Letter:In your cover letter, explain why you're passionate about systematic macro strategies. Discuss specific projects or models you've worked on that demonstrate your expertise in statistical and machine learning methodologies.
Showcase Your Achievements:Include quantifiable achievements in your application. For example, mention the performance metrics of the trading models you've developed, such as information ratios or risk-adjusted returns, to illustrate your success.
Prepare for Technical Questions:Be ready to discuss your technical skills and methodologies during the interview process. Brush up on time-series modelling, econometric analysis, and backtesting techniques, as these are crucial for the role.
How to prepare for a job interview at Eka Finance
✨Showcase Your Technical Skills
Be prepared to discuss your programming proficiency in Python and/or C#. Bring examples of past projects where you've implemented statistical or machine learning methodologies. This will demonstrate your hands-on experience and technical capabilities.
✨Discuss Your Research Experience
Highlight your background in quantitative macro research or portfolio management. Be ready to share specific instances where you've generated alpha and deployed strategies, as this aligns closely with the role's requirements.
✨Prepare for Technical Questions
Expect questions on time-series modelling, econometric analysis, and backtesting techniques. Brush up on these topics and be ready to explain your thought process and methodologies clearly.
✨Emphasise Collaboration Skills
Since the role involves working in a research-driven environment, illustrate your ability to collaborate effectively. Share examples of how you've worked with teams to enhance models or improve portfolio construction techniques.
