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- Tasks: Build and improve sports prediction models while analysing terabytes of data.
- Company: Join a leading provider of sports betting brokerage software based in London.
- Benefits: Enjoy flexible working hours and opportunities for career progression.
- Why this job: Be part of a dynamic team testing hypotheses in live markets with real impact.
- Qualifications: Postgraduate qualifications in statistics preferred; passion for sports is essential.
- Other info: Ideal for graduates or juniors looking to kickstart their quantitative developer career.
The predicted salary is between 28800 - 48000 £ per year.
Graduate/Junior Quantitative Analyst is required for one of the leading providers of sports betting brokerage software in the world. The company is based in London and offers flexible working hours. You will be working with terabytes of data, and will be part of a team that can quickly run experiments at scale in the markets, allowing the company to test their hypotheses in a live environment.
As Graduate Quantitative Analyst you will need:
- An interest in sports or competitive games
- Postgraduate qualifications in statistics are preferred.
Your day-to-day duties and responsibilities will include, but won’t be limited to:
- Building and improving sports prediction models
- Researching recent advances in Bayesian updating to better extract signals from noisy data
- Opportunities to progress your quantitative developer career
Implementation Analyst (Hybrid) employer: Venture Up
Contact Detail:
Venture Up Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Implementation Analyst (Hybrid)
✨Tip Number 1
Familiarise yourself with the latest trends in sports analytics and betting. Understanding how data is used to predict outcomes in sports can give you an edge during interviews, showing your genuine interest in the field.
✨Tip Number 2
Brush up on your statistical skills, especially in Bayesian methods. Being able to discuss recent advances in this area will demonstrate your technical knowledge and readiness for the role.
✨Tip Number 3
Network with professionals in the sports betting industry. Attend relevant meetups or webinars to connect with others in the field, which could lead to valuable insights and potential referrals.
✨Tip Number 4
Prepare to discuss real-world applications of your analytical skills. Think of examples where you've successfully used data to solve problems or improve processes, as this will highlight your practical experience.
We think you need these skills to ace Implementation Analyst (Hybrid)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant skills and experiences related to quantitative analysis and sports betting. Emphasise any postgraduate qualifications in statistics and any projects or coursework that demonstrate your analytical abilities.
Craft a Compelling Cover Letter: In your cover letter, express your passion for sports and competitive games. Discuss why you are interested in the role and how your background in statistics can contribute to building and improving sports prediction models.
Showcase Relevant Projects: If you have worked on any projects involving data analysis, Bayesian updating, or predictive modelling, be sure to include these in your application. Provide specific examples of how you approached problems and the outcomes of your work.
Proofread Your Application: Before submitting your application, carefully proofread all documents for spelling and grammatical errors. A polished application reflects your attention to detail, which is crucial for a role involving data analysis.
How to prepare for a job interview at Venture Up
✨Show Your Passion for Sports
Since the role involves sports betting, it's crucial to demonstrate your genuine interest in sports or competitive games. Be prepared to discuss your favourite sports, teams, or any relevant experiences that showcase your enthusiasm.
✨Highlight Your Statistical Knowledge
With a preference for postgraduate qualifications in statistics, make sure to emphasise your academic background and any relevant projects. Discuss specific statistical methods or tools you are familiar with, especially those related to Bayesian updating.
✨Prepare for Technical Questions
Expect technical questions related to data analysis and modelling. Brush up on your knowledge of sports prediction models and be ready to explain how you would approach building or improving them using real-world examples.
✨Demonstrate Problem-Solving Skills
The company values the ability to run experiments at scale and test hypotheses. Prepare to discuss past experiences where you successfully solved complex problems or made data-driven decisions, showcasing your analytical thinking.
