Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Join a leading investment platform to develop innovative equity trading strategies.
- Company: Global investment platform known for its cutting-edge research and collaborative culture.
- Benefits: Competitive salary, flexible work locations, and opportunities for professional growth.
- Why this job: Make an impact in finance by leveraging data science and quantitative research.
- Qualifications: Strong programming skills in Python and C++, with experience in systematic trading.
- Other info: Fast-paced environment with a focus on collaboration and continuous learning.
The predicted salary is between 36000 - 60000 £ per year.
We are supporting a leading global investment platform in hiring a highly skilled Quantitative Researcher. This role will focus on building and enhancing a market-microstructure-driven research framework for the systematic trading of global equity strategies. The ideal candidate will combine strong statistical and programming expertise with experience handling large financial datasets in a fast-paced, research-driven trading environment.
Key Responsibilities
- Strategy Research & Development
- Collaborate closely with the Senior Portfolio Manager to design and refine systematic global equities strategies.
- Contribute to idea generation, hypothesis testing, and alpha research.
- Conduct end-to-end research including data gathering, cleaning, feature creation, modeling, and backtesting.
- Data Engineering & Market Microstructure Research
- Work hands-on with multiple exchange data sets, ensuring high-quality data pipelines through assessing, cleaning, and building features.
- Analyze large, complex datasets using advanced statistical learning techniques and market-microstructure methods.
- Model Implementation
- Implement scalable, flexible, and efficient data-extraction frameworks using existing tools.
- Optimize Python and C++ code to support high-scale systematic research workflows.
- Create new data features and extend existing research infrastructure.
Required Technical Skills
- Strong expertise in Python (data analysis, scientific computing, statistical modeling).
- Proficiency with modern data science tooling: pandas, numpy, sklearn, Jupyter.
- Experience with C++ (preferred for feature creation and performance-critical components).
- Strong understanding of:
- Quantitative finance
- Probability theory
- Regression and statistical modelling
- Mathematical foundations behind systematic trading strategies
- Ability to clearly communicate complex research outputs to stakeholders.
Preferred Experience
- 2+ years working in a systematic trading environment, ideally focused on equities.
- Experience handling and transforming multiple vendor or exchange datasets, including assessing, cleaning, and creating predictive features.
- Track record of collaborating with PMs, engineers, and researchers in a fast-paced, iterative environment.
Highly Valued Attributes
- Strong intuition for the predictive power of features and datasets.
- Exceptionally rigorous, detail-oriented, and self-driven approach to research.
- Ability to work independently while contributing to a collaborative research environment.
- Curiosity, intellectual agility, and motivation to grow rapidly.
Quantitative Researcher - Systematic Equities - Global in London employer: Marlin Selection
Contact Detail:
Marlin Selection Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Researcher - Systematic Equities - Global in London
✨Tip Number 1
Network like a pro! Reach out to professionals in the quantitative finance space on LinkedIn or at industry events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python and C++. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your statistical modelling and market microstructure knowledge. Practice explaining complex concepts clearly, as communication is key in this field.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you, and applying directly can give you an edge in the hiring process.
We think you need these skills to ace Quantitative Researcher - Systematic Equities - Global in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of Quantitative Researcher. Highlight your experience with statistical modelling, Python, and any relevant projects that showcase your skills in handling large datasets. We want to see how you fit into our world!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about systematic trading and how your background aligns with our needs. Be sure to mention any specific experiences that relate to market microstructure or quantitative finance.
Showcase Your Technical Skills: Don’t hold back on showcasing your technical prowess! Include specific examples of your work with Python, C++, and data science tools like pandas and numpy. We love seeing how you've applied these skills in real-world scenarios, especially in fast-paced environments.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates. Plus, it’s super easy!
How to prepare for a job interview at Marlin Selection
✨Know Your Data Inside Out
Make sure you’re familiar with the types of financial datasets you’ll be working with. Brush up on your data cleaning and feature creation skills, as you might be asked to discuss how you would handle large datasets during the interview.
✨Show Off Your Coding Skills
Since Python and C++ are key for this role, be prepared to demonstrate your coding abilities. You could be asked to solve a problem on the spot, so practice coding challenges related to data analysis and statistical modelling beforehand.
✨Understand Market Microstructure
Dive deep into market microstructure concepts. Be ready to discuss how these principles apply to systematic trading strategies, as this knowledge will set you apart from other candidates who may not have the same level of understanding.
✨Communicate Clearly and Confidently
You’ll need to explain complex research outputs to stakeholders, so practice articulating your thoughts clearly. Use examples from your past experiences to illustrate your points, and don’t shy away from discussing your collaborative work with PMs and engineers.