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- Tasks: Develop predictive models for global sports events and collaborate with a dynamic team.
- Company: Join a thriving sports trading firm known for its innovative approach and strong team culture.
- Benefits: Enjoy a competitive salary, biannual bonuses, gym access, and a flexible work environment.
- Why this job: Be part of a close-knit team that values autonomy, innovation, and work-life balance.
- Qualifications: MSc or PhD in STEM, 3-10 years of relevant experience, and strong Python skills required.
- Other info: Flexible interview process and sponsorship available for exceptional candidates.
The predicted salary is between 56000 - 104000 £ per year.
Salary: £70,000 - £130,000 with a 20% bonus (paid biannually) + benefits
Location: Central London - 5 days a week onsite but very flexible
Join a successful growing sports trading firm as a Quantitative Analyst, working on predictive modelling and global trading strategies across football, cricket, US sports, and more.
ROLE AND RESPONSIBILITIES- Join a close-knit, high-performing technical team of ~20 within a 50–60 person investment trading business
- Develop predictive models to forecast outcomes of global sporting events
- Work in a flexible, fluid structure with strong autonomy, ownership, and work-life balance
- Collaborate cross-functionally across teams and contribute to an innovative, evolving research environment
- Take advantage of a unique benefits culture – including gym access during work hours and strong team retention
- MSc or PhD in a STEM-related subject (e.g., Maths, Statistics, Engineering)
- 5-10 years’ experience in quant/research-heavy roles (will consider strong candidates from 3 years)
- Excellent tenure: ideally 3–5 years at previous companies
- Strong programming skills in Python (R also a plus)
- Deep understanding of mathematical/statistical modelling
- Interest in sports – background in sports trading is a bonus, but not required
- Strong problem-solving mindset with the ability to reason through complex tasks
- No experience in credit risk (not relevant to this role)
- Onsite, flexible interviews (can accommodate out-of-hours)
- Entire process is flexible and candidate-led - no rigid structure
- Sponsorship is available for strong candidates!
Apply below!
Quantitative Analyst employer: LinkedIn
Contact Detail:
LinkedIn Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Analyst
✨Tip Number 1
Familiarise yourself with the latest trends in sports trading and predictive modelling. Being able to discuss current events or recent developments in the sports industry during your interview can demonstrate your genuine interest and knowledge, making you a more appealing candidate.
✨Tip Number 2
Brush up on your programming skills, especially in Python. Consider working on personal projects or contributing to open-source projects that showcase your ability to develop predictive models, as this practical experience can set you apart from other candidates.
✨Tip Number 3
Prepare to discuss your problem-solving approach in detail. Think of specific examples where you've tackled complex tasks in previous roles, as this will help illustrate your analytical mindset and ability to thrive in a fast-paced environment.
✨Tip Number 4
Network with professionals in the sports trading and quantitative analysis fields. Attend relevant meetups or online forums to connect with others in the industry, which could lead to valuable insights and potentially even referrals for the position at StudySmarter.
We think you need these skills to ace Quantitative Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in quantitative analysis, programming skills, and any sports-related projects. Use specific examples to demonstrate your expertise in predictive modelling and statistical analysis.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for sports and quantitative analysis. Explain why you are interested in this role and how your background aligns with the company's goals. Be sure to mention any relevant experience in sports trading or similar fields.
Highlight Technical Skills: Emphasise your programming skills, particularly in Python and R, as well as your understanding of mathematical and statistical modelling. Provide examples of projects where you've successfully applied these skills to solve complex problems.
Showcase Problem-Solving Abilities: In your application, include instances where you've tackled challenging problems in previous roles. Describe your thought process and the outcomes of your solutions to demonstrate your strong problem-solving mindset.
How to prepare for a job interview at LinkedIn
✨Showcase Your Technical Skills
As a Quantitative Analyst, your programming skills in Python are crucial. Be prepared to discuss your experience with coding and any relevant projects you've worked on. Consider bringing examples of your predictive models or statistical analyses to demonstrate your expertise.
✨Demonstrate Your Problem-Solving Abilities
This role requires a strong problem-solving mindset. During the interview, be ready to tackle hypothetical scenarios or case studies that test your analytical thinking. Explain your thought process clearly and how you approach complex tasks.
✨Express Your Passion for Sports
While a background in sports trading is a bonus, showing genuine interest in sports can set you apart. Discuss your favourite sports, teams, or any personal experiences related to sports analytics. This will help you connect with the interviewers and show your enthusiasm for the industry.
✨Prepare for a Flexible Interview Process
The interview process is candidate-led and flexible, so take advantage of this. Think about what aspects of your experience you want to highlight and prepare questions that reflect your interests in the role and the company culture. This will demonstrate your proactive nature and engagement.
