At a Glance
- Tasks: Develop cutting-edge statistical models to revolutionise sports betting.
- Company: Join a dynamic team at the forefront of the sports betting industry.
- Benefits: Competitive salary, supportive environment, and impactful projects.
- Other info: 5+ years experience in quantitative roles; mentoring opportunities available.
- Why this job: Shape the future of sports betting with innovative data-driven methodologies.
- Qualifications: PhD, Masters, or Bachelor's in STEM; proficiency in C# and Python.
The predicted salary is between 60000 - 80000 £ per year.
Join our team and shape the future of sports betting! We're seeking a highly motivated and innovative Quantitative Analyst to develop and maintain cutting-edge statistical models. You'll play a crucial role in enhancing our market offerings and driving our success in the dynamic world of sports betting. This is an opportunity to leverage your expertise in data science, machine learning, and AI to build models that predict outcomes, manage risk, and unlock new possibilities in micro-markets and derivatives.
A taster of what you will be involved with:
- Core Sports Betting Models: Develop and refine models for predicting match outcomes, incorporating advanced statistical methods, machine learning algorithms, and AI techniques.
- Player Statistics Models: Build and maintain sophisticated models that analyse player performance and predict individual contributions, opening up exciting new betting markets.
- Risk Management Models: Design and implement robust risk models to optimize our exposure and ensure the long-term sustainability of our operations.
- Market Expansion: Contribute to the development of innovative market offerings, including derivatives and micro-markets, by creating the necessary underlying models.
- Technology Modernization: Collaborate on the modernization of our modelling technologies, exploring and implementing new tools and platforms to enhance efficiency and scalability.
- Data-Driven Innovation: Contribute to the development of new data-driven methodologies, pushing the boundaries of what's possible in sports betting analytics.
- Data Collaboration: Work closely with the data engineering team to optimize data storage and retrieval processes, ensuring seamless access to the information needed for model development.
- Data Acquisition: Identify and collect relevant data sources to fuel model development and improvement.
- Knowledge Sharing: Document model methodologies clearly and concisely, effectively communicating complex technical concepts to both technical and non-technical stakeholders across the business.
- Performance Analysis: Collaborate with the performance analysis team to identify areas where models can be improved and contribute to the ongoing refinement of our analytical tools.
What we are looking for:
- You are a highly analytical and results-oriented individual with a passion for sports and a deep understanding of quantitative modelling.
- You thrive in a fast-paced environment and are eager to contribute to a team that is pushing the boundaries of sports betting analytics.
Education: PhD, Masters, or Bachelor’s degree in a STEM field (e.g., Mathematics, Statistics, Computer Science, Physics, Engineering).
Programming Skills: Proficiency in C# and Python is essential.
Modelling Expertise: Strong knowledge of statistical and machine learning modelling techniques.
Communication Skills: Excellent communication skills, with the ability to clearly explain complex technical information to diverse audiences.
Industry Knowledge: A solid understanding of the sports betting industry, sports trading, and sports modelling.
Problem-Solving: Demonstrated ability to solve complex problems and provide clear justifications for chosen methodologies.
Modelling Experience: Proven experience in building and deploying mathematical models.
Data Skills: Proficient in data retrieval and statistical analysis.
Experience: 5+ years of experience in a quantitative role.
Bonus Points: Experience working in the sports betting industry. Mentoring and team leadership skills. Experience developing quantitative models using machine learning and AI. Strong knowledge and skills in data engineering (SQL).
What we offer:
- A chance to be part of a dynamic and innovative team at the forefront of the sports betting industry.
- The opportunity to work on challenging and impactful projects.
- A competitive salary and benefits package.
- A collaborative and supportive work environment.
If you're ready to take your quantitative skills to the next level and revolutionize the world of sports betting, we encourage you to apply!
Senior Quantitative Data Analyst in London employer: Betsson Group
Sporting Solutions is an exceptional employer that fosters a collaborative and innovative work culture, perfect for those looking to make a significant impact in the tech-driven sports betting industry. With a strong focus on employee growth, you will have the opportunity to shape the future of DevOps while enjoying benefits such as hybrid working, competitive annual leave, and a supportive health care scheme. Join us in a dynamic environment where your expertise in .NET and DevOps will be valued and rewarded.
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We think this is how you could land Senior Quantitative Data Analyst in London
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We think you need these skills to ace Senior Quantitative Data Analyst in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
