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- Tasks: Use advanced stats and machine learning to analyse sports data for betting insights.
- Company: Dynamic sports analytics firm based in London, focused on innovation.
- Benefits: Competitive salary, flexible work environment, and opportunities for growth.
- Why this job: Join a fast-paced startup and make a real impact in the sports betting industry.
- Qualifications: Degree in mathematics, experience in sports betting, and skills in Bayesian stats, SQL, and Python.
- Other info: Autonomous role with exciting challenges and career advancement potential.
The predicted salary is between 36000 - 60000 £ per year.
A dynamic sports analytics firm in London is seeking a skilled Quantitative Analyst to deliver innovative solutions to the sports betting industry. You will leverage advanced statistical models and machine learning to interpret complex sports data, providing insightful analytics.
Ideal candidates possess:
- a mathematics-based degree
- extensive experience in the sports betting realm
- expertise in Bayesian statistics, SQL, and Python
This role requires autonomy in modeling efforts within a fast-paced startup environment.
Quantitative Analyst, Sports Betting - Bayesian ML & Risk employer: Venture Up
Contact Detail:
Venture Up Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Analyst, Sports Betting - Bayesian ML & Risk
✨Tip Number 1
Network like a pro! Reach out to folks in the sports betting industry on LinkedIn or at events. We all know that sometimes it’s not just what you know, but who you know that can land you that dream role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects in Bayesian statistics and machine learning. We want to see how you tackle real-world problems, so make sure to highlight your best work.
✨Tip Number 3
Prepare for the interview like it’s game day! Brush up on your SQL and Python skills, and be ready to discuss your thought process behind your models. We love candidates who can articulate their approach clearly.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we’re always on the lookout for passionate individuals who are eager to innovate in the sports analytics space.
We think you need these skills to ace Quantitative Analyst, Sports Betting - Bayesian ML & Risk
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with Bayesian statistics, SQL, and Python in your application. We want to see how you can leverage these skills to tackle challenges in the sports betting industry.
Tailor Your Application: Don’t just send a generic CV! Customise your application to reflect your understanding of the role and our company. We love seeing candidates who take the time to connect their experiences with what we do at StudySmarter.
Be Clear and Concise: When writing your application, keep it straightforward. We appreciate clarity, so make sure your points are easy to understand and directly related to the job description. This helps us see your thought process!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Venture Up
✨Know Your Stats
Brush up on your knowledge of Bayesian statistics and how it applies to sports betting. Be ready to discuss specific models you've worked with and how they impacted decision-making in previous roles.
✨Showcase Your Coding Skills
Prepare to demonstrate your proficiency in SQL and Python. You might be asked to solve a problem on the spot, so practice coding challenges related to data analysis and manipulation beforehand.
✨Understand the Industry
Familiarise yourself with current trends in sports analytics and betting. Being able to discuss recent developments or innovations in the field will show your passion and commitment to the industry.
✨Be Ready for Autonomy
Since this role requires independence in modelling efforts, think of examples where you've successfully worked autonomously. Highlight your problem-solving skills and how you manage projects without constant supervision.
