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For Companies At a Glance
- Tasks: Design and implement cutting-edge trading models using advanced statistical and mathematical techniques.
- Company: Global proprietary trading firm blending technology with quantitative research.
- Benefits: Competitive salary, dynamic work environment, and opportunities for professional growth.
- Why this job: Join a fast-paced team and make an impact in global financial markets.
- Qualifications: PhD in a quantitative field and strong programming skills in Python or similar languages.
- Other info: Collaborative culture with exposure to diverse asset classes and innovative technologies.
The predicted salary is between 43200 - 72000 £ per year.
Our client, are a global proprietary trading firm that combines sophisticated technology with deep quantitative research to deploy capital across global financial markets.
Role Overview
As a Quantitative Analyst, you will be at the heart of the trading and research efforts, designing and implementing statistical and mathematical models to identify and capitalise on market inefficiencies. You will work closely with traders, developers, and other quants in a fast-paced, intellectually demanding environment.
Key Responsibilities
- Research, develop, and optimise trading models using large and complex datasets
- Design and implement statistical, mathematical, and machine learning algorithms for signal generation and risk modeling
- Perform backtesting and performance evaluation of strategies across various asset classes (equities, futures, options, FX, crypto, etc.)
- Collaborate with technologists and traders to deploy models into production and monitor live trading systems
- Contribute to portfolio construction, alpha combination, and execution optimization
Required Qualifications
- PhD in Mathematics, Physics, Statistics, Computer Science, Engineering, or related quantitative field
- Strong foundation in probability, statistics, stochastic processes, optimization, and/or numerical methods
- Proficient programming skills in Python, C++, R, or MATLAB (Python preferred)
- Demonstrated experience working with large datasets, data cleaning, and analysis
- Familiarity with financial markets and instruments is a plus but not mandatory
- Exceptional problem-solving skills and attention to detail
- Ability to communicate complex ideas clearly and effectively
Desirable Experience (not required but a plus)
- Experience in quantitative finance, algorithmic trading, or financial data analysis
- Knowledge of machine learning frameworks and tools (e.g., scikit-learn, TensorFlow, PyTorch)
- Exposure to high-frequency data and time-series analysis
- Publications in peer-reviewed journals or participation in academic competitions (e.g., Kaggle, Olympiads)
Quantitative Analyst employer: Block MB
Contact Detail:
Block MB Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Analyst
✨Tip Number 1
Network like a pro! Reach out to professionals in the quantitative finance space on LinkedIn or at industry events. We can’t stress enough how valuable personal connections can be in landing that dream role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, models, and any relevant analyses you've done. This is your chance to demonstrate your expertise beyond just a CV, so let’s make it shine!
✨Tip Number 3
Prepare for those interviews! Brush up on your technical skills and be ready to discuss your thought process behind model development and problem-solving. We recommend practicing with friends or using mock interview platforms.
✨Tip Number 4
Apply through our website! We’ve got a streamlined application process that makes it easy for you to showcase your talents directly to us. Don’t miss out on the opportunity to join our innovative team!
We think you need these skills to ace Quantitative Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Quantitative Analyst role. Highlight your programming skills, especially in Python, and any relevant projects or research you've done in quantitative finance.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about quantitative analysis and how your background makes you a great fit. Be specific about your experience with statistical models and data analysis, and don’t forget to mention any collaborative projects you've worked on.
Showcase Your Problem-Solving Skills: In your application, give examples of how you've tackled complex problems in the past. Whether it's through academic projects or real-world experience, we want to see your analytical thinking in action!
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people!
How to prepare for a job interview at Block MB
✨Know Your Models Inside Out
As a Quantitative Analyst, you'll be expected to discuss your models in detail. Make sure you can explain the statistical and mathematical principles behind them, as well as how you've optimised them using large datasets. Brush up on your backtesting methods and be ready to share specific examples of your work.
✨Brush Up on Programming Skills
Since programming is key for this role, ensure you're comfortable with Python, C++, R, or MATLAB. Practise coding problems related to data analysis and algorithm implementation. You might even want to prepare a small project or two that showcases your skills, as it could come in handy during technical discussions.
✨Understand Financial Markets
While familiarity with financial markets isn't mandatory, having a basic understanding can set you apart. Read up on different asset classes like equities, futures, and options. Being able to discuss current market trends or recent news can demonstrate your interest and engagement in the field.
✨Communicate Clearly
You'll need to convey complex ideas effectively, so practise explaining your work to someone without a technical background. Use clear language and avoid jargon where possible. This will not only help you in the interview but also in collaborating with traders and technologists once you land the job.
