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- Tasks: Analyse data sets and develop predictive trading models with cutting-edge technology.
- Company: Global quantitative research firm in the heart of Greater London.
- Benefits: Competitive salary, medical insurance, pension scheme, and more.
- Why this job: Join a dynamic team and innovate in the world of trading.
- Qualifications: Master's or PhD in a relevant field with trading strategy experience.
- Other info: Collaborative environment with opportunities for professional growth.
The predicted salary is between 43200 - 72000 £ per year.
A global quantitative research firm in Greater London seeks Quantitative Researchers to analyze data sets and develop predictive trading models. The role involves collaboration with traders and developers, utilizing programming skills in C++ and Python, and applying statistical analysis.
Candidates should have a Master's or PhD in a relevant field and experience with trading strategies.
The firm offers competitive benefits, including medical insurance and a pension scheme.
Quantitative Researcher - Trading Team & ML Innovation employer: Jump Trading
Contact Detail:
Jump Trading Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Researcher - Trading Team & ML Innovation
✨Tip Number 1
Network like a pro! Reach out to professionals in the trading and quantitative research space on LinkedIn. A friendly message can go a long way in getting your foot in the door.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your predictive models or any relevant projects you've worked on. This is your chance to demonstrate your programming prowess in C++ and Python.
✨Tip Number 3
Prepare for those interviews! Brush up on your statistical analysis and trading strategies. We recommend practising common interview questions and even doing mock interviews with friends.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Quantitative Researcher - Trading Team & ML Innovation
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your programming skills in C++ and Python. We want to see how you can apply these languages to develop predictive trading models, so don’t hold back on showcasing your experience!
Talk About Your Experience: If you've got a Master’s or PhD, let us know! Share any relevant projects or research you've done, especially if it relates to trading strategies. This is your chance to shine and show us what you can bring to the table.
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate well-structured applications that get straight to the heart of your qualifications and experiences. Remember, less is often more!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Jump Trading
✨Know Your Data
Before the interview, brush up on your data analysis skills. Be prepared to discuss specific data sets you've worked with and how you applied statistical methods to derive insights. This will show your potential employer that you can hit the ground running.
✨Showcase Your Programming Skills
Since the role requires proficiency in C++ and Python, make sure you can talk about your experience with these languages. Bring examples of projects where you used them to develop predictive models or trading strategies. If possible, prepare to solve a coding challenge during the interview.
✨Understand Trading Strategies
Familiarise yourself with various trading strategies and be ready to discuss how you would approach developing new ones. This could involve explaining your thought process behind a model you've created or how you would adapt existing strategies based on market conditions.
✨Collaborate and Communicate
This role involves working closely with traders and developers, so highlight your teamwork and communication skills. Prepare examples of past collaborations and how you effectively communicated complex ideas to non-technical team members. This will demonstrate your ability to fit into their team dynamic.
