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For Companies At a Glance
- Tasks: Develop investment models and analyze market behavior using quantitative techniques.
- Company: Join a cutting-edge finance firm focused on data-driven investment strategies.
- Benefits: Collaborate with engineers, attend academic seminars, and gain insights from industry leaders.
- Why this job: Perfect for those passionate about statistics and machine learning in a dynamic environment.
- Qualifications: Degree in a technical field and programming skills required; all experience levels welcome.
- Other info: Send your CV to quants@ekafinance.com to apply!
The predicted salary is between 36000 - 60000 £ per year.
Job Description
Key Responsibilities:
- Design and develop systematic trading strategies with holding periods ranging from intraday to several weeks, with a focus on macro-driven relative value or CTA (Commodity Trading Advisor) approaches.
- Conduct in-depth quantitative research and signal generation using advanced statistical and machine learning techniques to identify inefficiencies in macro markets.
- Implement, back-test, and optimize systematic models to ensure robustness and adaptability to changing market conditions.
- Leverage extensive experience in macro asset classes and systematic trading to refine risk management and portfolio construction techniques.
- Stay ahead of market developments and advancements in quantitative finance, integrating cutting-edge methodologies into the research process.
- Work closely with trading, risk, and technology teams to align research insights with business objectives.
- Utilize Python and relevant data science/machine learning libraries to develop, test, and deploy strategies efficiently.
Qualifications & Experience:
- 5+ years of direct experience in macro systematic trading, with a proven track record in quantitative research or trading across commodities, FX, rates, or equity indexes.
- Strong background in mid to low frequency systematic strategies, particularly macro-focused relative value or CTA trading.
- Advanced degree (Master’s or PhD) in a quantitative field such as Mathematics, Statistics, Physics, Computer Science, or Financial Engineering.
- Expertise in Python and proficiency in handling large datasets, statistical modeling, and machine learning techniques.
- Deep understanding of macro market dynamics, quantitative finance, and numerical techniques relevant to systematic trading.
- Strong problem-solving abilities and experience in handling complex data analysis and model development.
- Excellent communication skills, with the ability to articulate research findings to both technical and non-technical stakeholders.
- Ability to work effectively within a collaborative, high-performance research team.
This role offers the opportunity to apply macro systematic expertise within a cutting-edge quantitative research environment. If you have a strong background in macro systematic trading strategies and are passionate about developing innovative quantitative models, we encourage you to apply.
Quant Researcher employer: Eka Finance
Contact Detail:
Eka Finance Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quant Researcher
✨Tip Number 1
Make sure to showcase your programming skills in languages like Python or C++ during the interview. Be prepared to discuss specific projects where you've applied these skills to solve complex problems.
✨Tip Number 2
Stay updated on the latest trends in quantitative finance and machine learning. Being able to discuss recent advancements or case studies can demonstrate your passion and knowledge in the field.
✨Tip Number 3
Network with professionals in the industry by attending relevant conferences and seminars. This can provide you with valuable insights and connections that may help you stand out during the application process.
✨Tip Number 4
Prepare to explain your research projects in detail, focusing on your methodology and findings. Being able to communicate complex ideas clearly is crucial for this role, so practice articulating your thought process.
We think you need these skills to ace Quant Researcher
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your technical or quantitative degree and any relevant experience in research projects. Emphasize your programming skills, especially in languages like Python or C++, as these are crucial for the role.
Showcase Your Research Experience: Detail any in-depth research projects you've undertaken, particularly those involving real-world data. Explain your methodologies and the outcomes to demonstrate your ability to apply quantitative techniques effectively.
Communicate Complex Ideas: Since the role requires clear communication of complex ideas, consider including a section in your CV or cover letter that illustrates how you've successfully communicated intricate concepts in past experiences.
Prepare a Strong PDF CV: Ensure your CV is well-structured and formatted as a PDF before sending it to quants@ekafinance.com. Double-check for any errors and make sure it aligns with the job requirements.
How to prepare for a job interview at Eka Finance
✨Showcase Your Technical Skills
Make sure to highlight your proficiency in programming languages like Python, C++, or Java. Be prepared to discuss specific projects where you've applied these skills, especially in the context of quantitative analysis.
✨Demonstrate Your Research Experience
Discuss any in-depth research projects you've undertaken, particularly those involving real-world data. Explain your methodology and the insights you gained, as this will showcase your ability to apply scientific methods in investment modeling.
✨Prepare for Technical Questions
Expect questions that test your understanding of machine learning and statistical techniques. Brush up on key concepts and be ready to explain how you would apply them to develop investment models.
✨Communicate Clearly
Since the role requires clear communication of complex ideas, practice explaining your past projects and findings in a straightforward manner. This will help demonstrate your ability to convey intricate concepts effectively.
