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- Tasks: Design and implement high-performance data pipelines and optimisation systems for trading.
- Company: Global multi-strategy investment firm with a strong track record in quantitative finance.
- Benefits: Competitive salary, dynamic work environment, and opportunities for professional growth.
- Why this job: Make a real impact on trading performance with cutting-edge technology and innovative strategies.
- Qualifications: 3+ years in development, strong Python skills, and familiarity with quantitative finance.
- Other info: Collaborative culture with a focus on entrepreneurial initiatives and career advancement.
The predicted salary is between 36000 - 60000 ÂŁ per year.
Our client is a global multiâstrategy investment firm with a long track record of success across quantitative, volatility, and fundamental equity strategies. They are seeking an experienced Quantitative Developer to join their Central Equity Quant Research (CEQR) team in London. This is an integrated function combining alpha modelling, transaction cost analysis, impactâaware execution, and portfolio construction & optimisation to drive firmwide P&L uplift.
The ideal candidate will possess strong software engineering fundamentals and familiarity with quantitative finance. Expertise in areas such as data pipelines, optimisation systems, and production trading infrastructure is highly valued. This role provides the opportunity to work directly on advanced data analysis, portfolio optimisation, platform development, and fully automated trading systems. Developers joining this group will have a direct and visible impact on trading performance. Our client welcomes individuals with a track record of building robust, scalable systems.
Key Responsibilities- Design and implement highâperformance data pipelines for largeâscale structured and unstructured financial datasets.
- Build productionâready optimisation systems for portfolio construction, execution, and risk management.
- Develop seamless integrations between research environments and live trading systems for efficient strategy deployment.
- Create scalable infrastructure for realâtime signal generation, order management, and position tracking across multiple trading desks.
- Collaborate with researchers to productionalise alpha models, impact calculations, and trading algorithms.
- Implement monitoring, testing, and validation frameworks to ensure reliability and model accuracy.
- Optimise computational performance and resource utilisation across distributed systems.
- Contribute to firmwide initiatives focused on execution quality and systematic trading infrastructure.
- Operate with an entrepreneurial mindset-balancing autonomy and collaboration-to identify and execute highâimpact technical initiatives.
- 3+ years of development experience within a systematic trading firm, hedge fund, investment bank, or technology company, with strong computer science and software engineering foundations.
- Deep proficiency in Python, and experience with at least one compiled language such as Java, C++, C#, or Rust.
- Competence in quantitative computing, including statistics, linear algebra, and working with large datasets. Our client seeks versatile engineers capable of bridging research and production.
- Ability to use modern AI development tools effectively while maintaining strong engineering fundamentals.
- While experience with data engineering and distributed systems is beneficial, our client prioritises strong general programming ability and versatility across technical domains.
Quant Developer | Central Equity Quant Research in London employer: Selby Jennings
Contact Detail:
Selby Jennings Recruiting Team
StudySmarter Expert Advice đ¤Ť
We think this is how you could land Quant Developer | Central Equity Quant Research in London
â¨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at events. A friendly chat can lead to opportunities that arenât even advertised yet.
â¨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to data pipelines and optimisation systems. This gives you a chance to demonstrate your expertise beyond just a CV.
â¨Tip Number 3
Prepare for technical interviews by brushing up on your Python and any compiled languages you know. Practice coding challenges and be ready to discuss your past projects in detail.
â¨Tip Number 4
Donât forget to apply through our website! Weâre always on the lookout for talented individuals who can make an impact, so make sure your application stands out.
We think you need these skills to ace Quant Developer | Central Equity Quant Research in London
Some tips for your application đŤĄ
Tailor Your CV: Make sure your CV highlights your experience in quantitative finance and software engineering. We want to see how your skills align with the role, so donât be shy about showcasing relevant projects or technologies you've worked with!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why youâre excited about the Quant Developer role and how your background makes you a perfect fit. We love seeing genuine enthusiasm for the work we do.
Showcase Your Technical Skills: Be specific about your programming expertise, especially in Python and any compiled languages. If youâve built data pipelines or optimisation systems, let us know! Weâre keen on candidates who can bridge research and production.
Apply Through Our Website: We encourage you to apply directly through our website. Itâs the best way for us to receive your application and ensures youâre considered for the role. Plus, it shows youâre proactive and ready to take the next step!
How to prepare for a job interview at Selby Jennings
â¨Know Your Tech Stack
Make sure youâre well-versed in Python and at least one compiled language like Java or C++. Brush up on your software engineering fundamentals, as theyâll likely ask you to demonstrate your coding skills. Practising coding challenges can really help you feel more confident.
â¨Understand Quantitative Finance
Familiarise yourself with key concepts in quantitative finance, such as alpha modelling and portfolio optimisation. Be prepared to discuss how youâve applied these concepts in previous roles, as this will show your potential employer that you can bridge the gap between research and production.
â¨Showcase Your Problem-Solving Skills
During the interview, expect to tackle real-world problems related to data pipelines and trading systems. Think aloud while solving these problems to demonstrate your thought process. This will give the interviewers insight into how you approach challenges and your ability to optimise performance.
â¨Prepare Questions About Their Systems
Have a few insightful questions ready about their current systems and initiatives. This shows your genuine interest in the role and helps you understand how you can contribute to their goals. Ask about their approach to execution quality and how they integrate research with live trading.