At a Glance
- Tasks: Research trading signals using data, build models, and analyse results.
- Company: Leading systematic trading firm with a focus on innovation.
- Benefits: Competitive salary, dynamic work environment, and hands-on experience.
- Other info: Great opportunity for ambitious graduates to grow in a fast-paced industry.
- Why this job: Dive into real trading challenges and make an impact with your coding skills.
- Qualifications: Technical degree and strong coding skills in Python, C++, or Java.
The predicted salary is between 30000 - 40000 £ per year.
- Research Developer - Graduate
- Amsterdam, London, Chicago or New York
Quant Capital is working with a leading systematic trading firm looking for a graduate Research Developer to join its trading research team.
This is a role for someone who wants to work on real trading problems, using statistics, machine learning and code to find signals in noisy market data.
You will be working with quantitative researchers on ideas that can move from research into live automated trading.
The focus is practical research. You will test hypotheses, build models, analyse results and help turn good ideas into robust trading strategies.
The role
- Research predictive signals using large, noisy financial datasets
- Build and test models for automated trading strategies
- Write production-quality code in Python, C++ or Java
- Analyse strategy performance and understand what is driving results
- Work with researchers to move ideas from prototype to live trading
- Improve datasets, tools and research workflows
- Take ownership of work from initial idea through to measured outcome
- What we are looking for
- Graduate from a highly technical degree such as computer science, maths, statistics, engineering or physics
- Strong knowledge of statistics, probability or machine learning
- Solid coding ability in Python, C++ or Java
- Genuine interest in systematic trading and markets
- Comfortable working with messy real-world data
- Ambitious, practical and focused on results
- Low ego and happy working both independently and in a small team
- Useful experience
- Internship in quant research, trading, data science or software engineering
- Time-series modelling, backtesting or signal research
- Machine learning applied to real-world datasets
- Personal projects involving markets, data or numerical research
This is a strong opportunity for a technically sharp graduate who wants to work close to trading, where research quality, coding ability and commercial impact are tightly linked.
All applications are handled in strict confidence.
Research Developer - Graduate in Slough employer: Quant Capital
Quant Capital is an excellent employer for those looking to thrive in the fintech sector, offering a vibrant work culture that fosters innovation and collaboration. With substantial training and development opportunities, employees can enhance their skills while enjoying a flexible hybrid work model in the heart of London. Join us to be part of a forward-thinking team that values growth and cutting-edge technology.
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We think this is how you could land Research Developer - Graduate in Slough
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We think you need these skills to ace Research Developer - Graduate in Slough
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Quant Capital. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Quant Capital
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
