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- Tasks: Develop cutting-edge betting solutions using statistical models and high-performance algorithms.
- Company: Join a dynamic team in the heart of London’s innovative betting industry.
- Benefits: Enjoy competitive salary, performance bonuses, health insurance, and gym memberships.
- Why this job: Make an impact in sports analytics while working with passionate professionals.
- Qualifications: Proficiency in Python or R with experience in football modelling is essential.
- Other info: Collaborative environment with regular team events and opportunities for growth.
The predicted salary is between 36000 - 60000 £ per year.
The successful candidate will join a team which develops betting solutions. These betting solutions entail the development of mathematical/statistical models and high-performance algorithms; efficient coding; automation of betting operations; data generation, acquisition, storage and manipulation; and performance analysis through back-testing and simulations.
Industry based experience of, and genuine proficiency in, Python or R or a similar programming language is essential. We are specifically looking for someone with industry experience creating football models.
Key Responsibilities- Acquire data from multiple data sources, filtering, cleaning and wrapping.
- Interpret data, analyse results using statistical techniques, and provide reports.
- Identify, analyse, and interpret trends or patterns in complex data sets.
- Work within the team to prioritise business and information needs.
- Identify process improvement opportunities.
- Design, build, test and deliver data processing and automation software.
- Statistical modelling and skills in data analytics.
- Experience creating and implementing football models.
- Strong attention to detail and ability to retain information.
- Adept using analytical programming languages such as R, Python, C++, etc. with at least 2 years commercial experience.
- BSc in mathematics, statistics, computer science, engineering or other quantitative discipline.
- Strong communication and collaboration skills.
- Positive ‘can do’ attitude, and ability to meet deadlines.
- Willingness to learn and adapt to new environments.
- Experience in the financial, betting, or gaming industries is a plus.
- Salary depending on experience.
- Annual discretionary performance bonus.
- 25 days holiday per annum, plus UK bank holidays.
- Private health & dental insurance.
- Optical cover through Aviva.
- Pension plan.
- Gympass membership to over 1900 gyms and wellness businesses.
- Breakfast bought in everyday and lunch bought in twice a week.
- Free coffee & snacks at the office.
- Regular team events & socials.
Quantitative Specialist- Football employer: White Swan Data
Contact Detail:
White Swan Data Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Specialist- Football
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those who work in football analytics. Attend meetups or webinars, and don’t be shy to slide into DMs on LinkedIn. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your football models and any relevant projects you've worked on. This is your chance to demonstrate your expertise in Python or R and how you can apply it to real-world scenarios. Make sure to highlight your analytical prowess!
✨Tip Number 3
Prepare for interviews by brushing up on your statistical modelling knowledge and coding skills. Be ready to discuss your past experiences and how they relate to the role. Practice common interview questions and think about how you can showcase your problem-solving abilities.
✨Tip Number 4
Don’t forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Tailor your application to highlight your experience with football models and your passion for data analytics. Let’s get you that dream job!
We think you need these skills to ace Quantitative Specialist- Football
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with football models and any relevant programming skills. We want to see how your background aligns with the role, so don’t be shy about showcasing your achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about football analytics and how your skills can contribute to our team. Keep it engaging and personal – we love a good story!
Showcase Your Technical Skills: Since we’re all about data and algorithms, make sure to mention your proficiency in Python or R. If you’ve worked on any projects that involved statistical modelling or automation, give us the details – we’re keen to hear about your hands-on experience!
Apply Through Our Website: We encourage you to apply directly through our website for a smoother process. It helps us keep track of applications and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at White Swan Data
✨Know Your Models Inside Out
Make sure you can discuss the football models you've created in detail. Be prepared to explain your methodology, the data sources you used, and how you interpreted the results. This shows not only your technical skills but also your passion for the sport.
✨Brush Up on Your Coding Skills
Since proficiency in Python or R is essential, take some time to review your coding skills before the interview. Be ready to tackle coding challenges or discuss your previous projects that involved automation and data processing.
✨Prepare for Data Analysis Questions
Expect questions that test your ability to analyse complex data sets. Practice explaining statistical techniques and how you've applied them in real-world scenarios. Use examples from your past experience to illustrate your analytical thinking.
✨Show Your Team Spirit
Collaboration is key in this role, so be ready to discuss how you've worked within a team in the past. Highlight any experiences where you prioritised business needs or identified process improvements, as this will demonstrate your ability to contribute positively to the team dynamic.
