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For Companies At a Glance
- Tasks: Design and manage high-performance trading strategies using advanced programming.
- Company: Join a leading hedge fund in London with cutting-edge technology and market data.
- Benefits: Enjoy flexible working, uncapped performance bonuses, and equity options.
- Why this job: Work in a fast-paced environment with direct impact on profits and innovative strategies.
- Qualifications: 2-5 years in algorithmic trading; strong programming skills in Python, C++, or Java required.
- Other info: Ideal for those passionate about quantitative finance and high-frequency trading.
The predicted salary is between 43200 - 72000 £ per year.
Job Description
Role Overview
We are seeking a highly skilled and driven Algorithmic Trader to join our client London-based trading team. The ideal candidate will design, implement, and manage high-performance trading strategies using quantitative methods and advanced programming. This is an opportunity to work in a fast-paced environment with direct PnL responsibility and access to state-of-the-art technology and market data.
Key Responsibilities
- Develop and deploy algorithmic trading strategies across global markets (equities, futures, FX, crypto, or fixed income)
- Perform in-depth statistical research and backtesting to evaluate strategy performance
- Monitor and optimize real-time trading systems and strategies
- Collaborate with quant researchers, developers, and risk teams to refine models and execution
- Ensure compliance with trading regulations and risk controls
- Generate new ideas for alpha generation and strategy diversification
Key Requirements
- 2–5 years of experience in quantitative or algorithmic trading, preferably with a proprietary trading firm, hedge fund, or tier-one bank
- Strong programming skills in Python, C++, or Java
- Proficiency in using data science libraries (NumPy, Pandas, scikit-learn) and backtesting frameworks
- Deep understanding of market microstructure and electronic execution
- Bachelor’s/Master’s/PhD in a quantitative field (e.g. Mathematics, Physics, Computer Science, Engineering)
- Strong grasp of probability, statistics, and linear algebra
- Ability to handle high-pressure, high-frequency environments with precision and accountability
Preferred Experience
- Experience with low-latency systems and infrastructure optimization
- Knowledge of FIX protocol, market data feeds, and exchange APIs
- Exposure to machine learning techniques for prediction and feature engineering
- Previous live trading experience with proven PnL
Compensation
- Base salary + performance bonus (uncapped, PnL-based)
- Equity/share options (where applicable)
- Pension, private healthcare, flexible working arrangements
Algorithmic Trader- Hedge Fund employer: Flynn and Chase
Contact Detail:
Flynn and Chase Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Algorithmic Trader- Hedge Fund
✨Tip Number 1
Network with professionals in the algorithmic trading space. Attend industry conferences, webinars, and meetups to connect with traders and quant researchers. Building relationships can lead to insider knowledge about job openings and company culture.
✨Tip Number 2
Stay updated on the latest trends and technologies in algorithmic trading. Follow relevant blogs, podcasts, and forums to understand what strategies are currently successful and what tools are being used. This knowledge can give you an edge during interviews.
✨Tip Number 3
Consider participating in trading competitions or hackathons. These events not only sharpen your skills but also provide tangible proof of your abilities. Plus, they can be a great way to meet potential employers and showcase your talent.
✨Tip Number 4
Familiarise yourself with the specific technologies and programming languages mentioned in the job description. If you're not already proficient in Python, C++, or Java, take some time to work on projects that demonstrate your skills in these areas, especially using data science libraries.
We think you need these skills to ace Algorithmic Trader- Hedge Fund
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in quantitative or algorithmic trading. Emphasise your programming skills in Python, C++, or Java, and any experience with data science libraries and backtesting frameworks.
Craft a Strong Cover Letter: In your cover letter, express your passion for algorithmic trading and detail how your background aligns with the key responsibilities of the role. Mention specific projects or strategies you've developed that demonstrate your skills.
Showcase Your Technical Skills: Include examples of your programming projects or any algorithms you've implemented. If you have experience with low-latency systems or machine learning techniques, make sure to highlight these as they are preferred qualifications.
Prepare for Technical Questions: Anticipate technical questions related to market microstructure, statistical methods, and programming challenges. Be ready to discuss your thought process and problem-solving approach during interviews.
How to prepare for a job interview at Flynn and Chase
✨Showcase Your Technical Skills
Be prepared to discuss your programming skills in Python, C++, or Java. Bring examples of past projects or trading strategies you've developed, and be ready to explain the algorithms and data science libraries you used.
✨Demonstrate Your Market Knowledge
Familiarise yourself with current market trends and recent developments in algorithmic trading. Be ready to discuss how these factors influence trading strategies and your approach to generating alpha.
✨Prepare for Technical Questions
Expect questions that test your understanding of probability, statistics, and linear algebra. Brush up on concepts related to market microstructure and electronic execution, as these are crucial for the role.
✨Highlight Your Experience with Backtesting
Discuss your experience with backtesting frameworks and statistical research. Be prepared to explain how you've evaluated strategy performance in the past and any insights gained from those analyses.
