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For Companies At a Glance
- Tasks: Analyse vast data sets to uncover market patterns and develop predictive trading models.
- Company: Join a leading global quantitative trading firm with a dynamic London office.
- Benefits: Enjoy comprehensive health insurance, paid leave, and a retirement plan with employer match.
- Why this job: Make an impact in the trading world while collaborating with top-tier professionals.
- Qualifications: Strong programming skills in C++/Python and a Master's or PhD in a related field.
- Other info: Thriving team environment with opportunities for growth and innovation.
The predicted salary is between 36000 - 60000 £ per year.
Overview
Jump’s London office is the hub for managing Jump’s substantial United Kingdom, European and expanding Middle Eastern operations, which includes all aspects of Jump’s robust activities, including quantitative research and development, trading, trading and back office systems development, and venture and strategic investments. Working in the London office has the feel of a smaller company with the benefits of being an integral part of one of the world’s leading global quantitative trading firms. Our Amsterdam office was born in 2018 as our first step into mainland Europe. Amsterdam is at the forefront of everyday European Trading events.
The quantitative trading teams at Jump Trading probe and examine the global markets, seeking to understand the complexities of various traded products and exchanges. They leverage their impeccable statistical analysis and data mining skills, using the results of their research to make forecasts and develop profitable predictive trading models.
Responsibilities
Quantitative Researchers collect and analyze tens of thousands of data sets, identify patterns and extract insights into the complexities in financial markets. Researchers lean heavily on statistical analysis, machine learning, and data engineering skills; applying the results of their research to forecasts and predictive trading models. Jump’s Quantitative Researchers are constantly collaborating with other scientists, traders, hardware and software developers, and market facing business teams to push for the best expression of our new ideas. Other duties as assigned or needed.
Qualifications
- Proven success with profitable trading strategies.
- Strong programming skills in C++/Python in a Linux environment.
- Working knowledge of forecasting and data mining techniques, such as linear and non-linear regression analysis, neural networks, or support vector machines.
- Strong experience developing statistical models in a trading environment.
- Proven success working with large data sets and developing statistical models.
- Fascinated and interested in advancing machine learning within the trading community.
- Possess strong familiarity with Python, R or MATLAB along with development skills to support research efforts.
- Masters or PhD in Statistics, Physics, Mathematics (or related subject).
- Desire to work within a collaborative, team-driven environment.
- Reliable and predictable availability
Benefits
- Medical, dental and vision insurance
- Group Term Life and AD&D Insurance
- Paid vacation plus paid holidays
- Retirement plan with employer match
- Paid parental leave
- Wellness Programs
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Quantitative Researcher | Trading team employer: P2P
Contact Detail:
P2P Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Researcher | Trading team
✨Tip Number 1
Network like a pro! Reach out to current or former employees at Jump Trading on LinkedIn. A friendly chat can give us insider info and maybe even a referral, which can really boost our chances.
✨Tip Number 2
Prepare for the technical interview! Brush up on your programming skills in C++ and Python, and be ready to discuss your experience with statistical models. We want to show them we’re not just good on paper but can also think on our feet.
✨Tip Number 3
Show off our passion for quantitative research! During interviews, share specific examples of how we've used data analysis to solve problems or develop trading strategies. Let’s make it clear that we live and breathe this stuff!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure our application gets seen by the right people. Plus, it shows we’re genuinely interested in being part of the Jump Trading team.
We think you need these skills to ace Quantitative Researcher | Trading team
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Quantitative Researcher role. Highlight your programming skills in C++/Python and any experience with statistical models or machine learning. We want to see how your background aligns with our needs!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about quantitative research and how your skills can contribute to our trading team. Keep it concise but impactful – we love a good story!
Showcase Your Projects: If you've worked on relevant projects, whether in academia or industry, make sure to mention them. We’re interested in seeing how you’ve applied your statistical analysis and data mining skills in real-world scenarios. Don’t hold back!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team at StudySmarter!
How to prepare for a job interview at P2P
✨Know Your Data Inside Out
Make sure you’re well-versed in the data sets relevant to quantitative research. Brush up on your statistical analysis techniques and be ready to discuss how you've applied them in past projects. This will show that you can hit the ground running.
✨Show Off Your Programming Skills
Since strong programming skills in C++/Python are crucial, prepare to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so practice coding challenges beforehand. Familiarity with Linux environments will also give you an edge.
✨Discuss Your Trading Strategies
Be prepared to talk about your experience with profitable trading strategies. Share specific examples of how you’ve used statistical models to make predictions and the outcomes of those strategies. This will highlight your practical knowledge and success in the field.
✨Emphasise Collaboration
Jump values teamwork, so be ready to discuss how you’ve collaborated with others in previous roles. Highlight any experiences where you worked alongside traders, developers, or other researchers to achieve a common goal. This will show you’re a great fit for their team-driven environment.
