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- Tasks: Develop alpha signals and models for mid-frequency equity strategies.
- Company: Join DRW, a dynamic firm prioritising innovation and integrity.
- Benefits: Competitive salary, collaborative environment, and opportunities for growth.
- Other info: Work closely with a Portfolio Manager in a fast-paced setting.
- Why this job: Make an impact in finance with cutting-edge quantitative research.
- Qualifications: 2-8 years of quant equities experience and strong Python skills.
The predicted salary is between 60000 - 80000 £ per year.
DRW is seeking a Quantitative Researcher in Greater London to focus on alpha generation and model development for mid-frequency equity strategies. The role involves collaboration with a Portfolio Manager, requiring 2-8 years of quant equities experience, strong programming skills in Python, and familiarity with diverse datasets. An advanced degree in a quantitative discipline is essential. Join DRW to work in a dynamic environment prioritising innovation and integrity.
Equity Quant Researcher: Alpha Signals & Live Trading in London employer: DRW
Contact Detail:
DRW Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Equity Quant Researcher: Alpha Signals & Live Trading in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at DRW or similar firms. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! If you've got some cool projects or models you've worked on, make sure to highlight them in conversations. Bring your Python prowess to the table and demonstrate how you can contribute to alpha generation.
✨Tip Number 3
Prepare for the technical grill! Brush up on your quantitative skills and be ready to tackle some brain teasers or coding challenges. We want to see how you think and solve problems, so practice makes perfect!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you're genuinely interested in joining our innovative team at DRW. Don’t miss out!
We think you need these skills to ace Equity Quant Researcher: Alpha Signals & Live Trading in London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your programming skills in Python and any relevant experience with quant equities. We want to see how you can contribute to our alpha generation and model development!
Tailor Your Application: Don’t just send a generic CV! Customise your application to reflect the specific requirements of the Equity Quant Researcher role. We love seeing candidates who take the time to align their experience with what we’re looking for.
Be Clear and Concise: When writing your application, keep it straightforward. We appreciate clarity and brevity, so make sure your key points stand out without unnecessary fluff.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at DRW
✨Know Your Quantitative Stuff
Make sure you brush up on your quantitative skills and concepts related to alpha generation and model development. Be ready to discuss your previous experiences in quant equities and how they relate to the role at DRW.
✨Show Off Your Python Skills
Since strong programming skills in Python are a must, prepare to demonstrate your coding abilities. You might be asked to solve a problem or explain your thought process while coding, so practice coding challenges beforehand.
✨Familiarise with Diverse Datasets
Get comfortable discussing various datasets you've worked with. Be prepared to explain how you’ve used them in your past roles, especially in relation to mid-frequency equity strategies. This will show your depth of knowledge and practical experience.
✨Emphasise Collaboration
As the role involves working closely with a Portfolio Manager, highlight your teamwork and collaboration skills. Share examples of how you’ve successfully worked in a team environment and contributed to collective goals in your previous positions.