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- Tasks: Develop and refine execution algorithms for equities trading.
- Company: Join a leading global trading firm known for its innovation in quant execution.
- Benefits: Enjoy competitive pay, career growth, and access to cutting-edge technology.
- Why this job: Be at the forefront of trading innovation and collaborate with top talent.
- Qualifications: Expertise in algorithmic execution, strong Python skills, and knowledge of equities markets required.
- Other info: This role offers a unique chance to lead in a dynamic trading environment.
The predicted salary is between 60000 - 84000 £ per year.
CW Talent Solutions is partnering with a leading global trading firm to hire an experienced Senior Quant Execution Trader to optimize execution strategies and drive trading performance across equities markets. This is a unique opportunity to work at the intersection of quantitative research, execution strategy, and technology in a cutting-edge trading environment.
The Role:
We are seeking a highly skilled Quant Execution Trader with a strong background in algorithmic execution. You’ll work closely with quants, traders, and developers to refine trading strategies and enhance execution performance.
Key Responsibilities:
- Develop and refine execution algorithms for equities trading
- Optimize market impact models and execution strategies to reduce slippage
- Conduct transaction cost analysis (TCA) to enhance trading performance
- Collaborate with developers and researchers to improve execution infrastructure
- Engage with exchanges, brokers, and liquidity providers to enhance access to liquidity
- Leverage quantitative models to drive best execution and trade efficiency
Preferred Experience:
- Expertise in market microstructure, execution algorithms, and TCA
- Strong programming skills in Python
- Experience with high-frequency trading (HFT) or systematic execution strategies
- Deep understanding of equities markets, order flow dynamics, and liquidity provisioning
- Strategic, analytical mindset with a passion for execution optimization
What’s in it for you?
- A chance to lead and innovate in quant execution trading
- Competitive compensation and strong career growth potential
- Access to cutting-edge trading technology and a collaborative quant team
- Work with a globally recognized trading firm at the forefront of execution innovation
Why Choose Us?
Our client is an industry leader in quant execution and algorithmic trading, known for its technological edge and advanced research infrastructure. If you’re ready to take execution trading to the next level, this is your opportunity.
Get in touch today!
Senior Quant Trader - Equities employer: CW Talent Solutions
Contact Detail:
CW Talent Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Quant Trader - Equities
✨Tip Number 1
Network with professionals in the trading and quantitative finance sectors. Attend industry conferences, webinars, or local meetups to connect with potential colleagues and learn about the latest trends in execution trading.
✨Tip Number 2
Familiarise yourself with the latest tools and technologies used in algorithmic trading. Being well-versed in platforms and programming languages like Python can set you apart from other candidates.
✨Tip Number 3
Stay updated on market microstructure and execution strategies by reading relevant research papers and articles. This knowledge will help you engage in meaningful discussions during interviews and demonstrate your expertise.
✨Tip Number 4
Prepare for technical interviews by practising problem-solving and coding challenges related to trading algorithms. This will not only boost your confidence but also showcase your analytical skills to potential employers.
We think you need these skills to ace Senior Quant Trader - Equities
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in algorithmic execution and quantitative trading. Emphasise your programming skills in Python and any relevant projects or roles that showcase your expertise in market microstructure and transaction cost analysis.
Craft a Compelling Cover Letter: In your cover letter, express your passion for execution optimisation and your strategic mindset. Mention specific examples of how you've developed or refined execution algorithms in the past, and how you can contribute to the firm's goals.
Highlight Relevant Experience: When detailing your work history, focus on your experience with high-frequency trading and systematic execution strategies. Use metrics to demonstrate your impact, such as improvements in trading performance or reductions in slippage.
Showcase Collaboration Skills: Since the role involves working closely with quants, traders, and developers, highlight any collaborative projects you've been part of. Discuss how you’ve engaged with exchanges, brokers, or liquidity providers to enhance trading performance.
How to prepare for a job interview at CW Talent Solutions
✨Showcase Your Quantitative Skills
Be prepared to discuss your experience with quantitative models and execution algorithms. Highlight specific projects where you've optimised trading strategies or reduced slippage, as this will demonstrate your expertise in the field.
✨Demonstrate Programming Proficiency
Since strong programming skills in Python are essential for this role, be ready to discuss your coding experience. You might even be asked to solve a coding problem during the interview, so brush up on your Python skills and be prepared to explain your thought process.
✨Understand Market Microstructure
Familiarise yourself with market microstructure concepts and how they relate to execution strategies. Be ready to discuss how you have applied this knowledge in previous roles, particularly in high-frequency trading or systematic execution.
✨Prepare for Technical Questions
Expect technical questions related to transaction cost analysis (TCA) and execution performance. Review key metrics and methodologies used in TCA, and be prepared to explain how you would approach enhancing trading performance through data analysis.
