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- Tasks: Analyse football data, develop models, and create insights for performance improvement.
- Company: Join a world-renowned football club focused on innovation and excellence in sports analytics.
- Benefits: Enjoy flexible working options and access to real-world sports data.
- Why this job: Make a meaningful impact in sports while collaborating with top footballers and experts.
- Qualifications: 3+ years in Data Science, strong Python skills, and experience with statistical modelling required.
- Other info: Opportunity for professional growth within a creative and collaborative team.
The predicted salary is between 36000 - 60000 £ per year.
This role is a unique opportunity for a Data Scientist to combine technical challenges with creativity in a collaborative, high-standard work environment. By joining this team, you’ll not only be part of a creative and open work culture focused on innovation and excellence but also have the chance to work with and collaborate with some of the most well-known footballers in the industry. This position offers significant opportunities for professional growth within sports analytics and the potential to impact sports performance through advanced technology, making it an ideal setting for those passionate about leveraging cutting-edge technology to make meaningful contributions in the world of sports analytics.
Key responsibilities for the role of Data Scientist include:
- Collect, clean, and process football-related data from various sources.
- Develop and implement statistical models and algorithms to analyze player performance and match outcomes.
- Create detailed reports and visualizations to communicate insights and recommendations to technical and non-technical stakeholders.
- Collaborate with football analysts, coaches, and other stakeholders to understand their needs and provide actionable insights.
- Stay updated with the latest trends and advancements in sports analytics and data science.
As the selected Data Scientist, your background will include:
- 3+ years industry experience in a Data Science role and a strong academic background.
- Python Data Science Stack: Advanced proficiency in Python, including pandas, NumPy, scikit-learn, and Jupyter Notebooks.
- Statistical & ML Modelling: Strong foundation in statistical analysis and proven experience applying a range of machine learning techniques to solve business problems (e.g., regression, classification, clustering, time-series forecasting). Practical experience with Keras or PyTorch is required.
- Full-Stack Deployment: Demonstrable experience taking models to production, including building and deploying APIs with FastAPI and using Vertex AI for ML workflows.
- Visualization & Communication: Ability to create clear visualizations and effectively communicate technical findings to non-technical stakeholders.
Highly desirable skills include:
- Football Analytics Domain: Significant plus if experienced with football datasets (event, tracking, etc.) and visualization libraries like mplsoccer.
- Advanced MLOps & Modelling: Deeper experience with the Vertex AI lifecycle (especially Pipelines) and advanced modelling techniques relevant to football (player valuation, tactical analysis).
- Bayesian Modelling: Experience with probabilistic programming (e.g., PyMC).
- Stakeholder Management: Proven success working directly with business stakeholders to define and deliver impactful solutions.
What They Offer:
- Work that impacts elite football performance and club-wide success.
- Access to real-world sports data and performance analytics.
- Flexible working options (hybrid/remote depending on role).
- Opportunity to grow with a digital-first team inside a world-renowned club.
Data Scientist employer: Singular Recruitment
Contact Detail:
Singular Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Familiarise yourself with the latest trends in sports analytics and data science. This will not only help you understand the industry better but also allow you to engage in meaningful conversations during interviews, showcasing your passion for the field.
✨Tip Number 2
Network with professionals in the sports analytics space, especially those who work with football data. Attend relevant meetups or online webinars to connect with potential colleagues and gain insights into the specific challenges they face.
✨Tip Number 3
Prepare to discuss your experience with Python and machine learning techniques in detail. Be ready to provide examples of how you've applied these skills to solve real-world problems, particularly in a sports context.
✨Tip Number 4
Showcase your ability to communicate complex data insights clearly. Practice explaining your past projects to non-technical audiences, as this skill is crucial for collaborating with coaches and analysts in the role.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science, particularly focusing on your proficiency with Python and any experience you have in sports analytics. Use specific examples to demonstrate your skills in statistical modelling and machine learning.
Craft a Compelling Cover Letter: In your cover letter, express your passion for sports analytics and how your background aligns with the role. Mention any experience you have working with football datasets and your ability to communicate technical findings to non-technical stakeholders.
Showcase Your Projects: If you have worked on relevant projects, especially those involving football analytics or machine learning, include them in your application. Provide links to your GitHub or portfolio where potential employers can see your work in action.
Highlight Collaboration Skills: Since the role involves collaboration with various stakeholders, emphasise your experience working in teams. Share examples of how you've successfully communicated insights to both technical and non-technical audiences.
How to prepare for a job interview at Singular Recruitment
✨Showcase Your Technical Skills
Be prepared to discuss your experience with the Python Data Science Stack, including libraries like pandas and scikit-learn. You might be asked to solve a technical problem on the spot, so brush up on your coding skills and be ready to demonstrate your proficiency.
✨Understand Football Analytics
Since this role is focused on sports analytics, having a solid understanding of football datasets and how they can be used to derive insights is crucial. Familiarise yourself with common metrics and analytics used in football to impress your interviewers.
✨Prepare for Collaboration Questions
This position involves working closely with analysts, coaches, and other stakeholders. Be ready to share examples of how you've successfully collaborated in the past, particularly in translating complex data into actionable insights for non-technical audiences.
✨Stay Updated on Industry Trends
Demonstrating your knowledge of the latest trends in sports analytics and data science will show your passion for the field. Research recent advancements and be prepared to discuss how they could apply to the role and the organisation.
