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- Tasks: Design and deploy data models to enhance football strategies and performance.
- Company: Join a world-renowned football club at the forefront of AI and data technology.
- Benefits: Flexible hybrid working model, access to high-value datasets, and career growth opportunities.
- Why this job: Make a real impact in elite football using advanced data science techniques.
- Qualifications: 3+ years as a Data Scientist with strong Python and statistical modelling skills.
- Other info: Collaborative environment with access to sports science teams and cross-disciplinary experts.
The predicted salary is between 50000 - 70000 £ per year.
This is a unique opportunity to work at the cutting edge of AI, data technology, and elite football analytics. As a Data Scientist, you’ll join a collaborative, high-performing team with a culture rooted in creativity, innovation, and excellence. In this role, you’ll design and deploy data models that power decision-making across every area of the club — from strategy, tactics, recruitment, and performance, to pre- and post-match analysis. You'll also play a key role in supporting the club’s commercial operations, including e-commerce and fan engagement. If you’re passionate about using advanced data science to drive real-world impact in sport, this is the role for you.
Key Responsibilities
- Develop and apply statistical models and algorithms to analyse player performance, match outcomes, and tactical insights.
- Collect, clean, and process football-related data from diverse sources.
- Build clear, compelling visualizations and deliver insights to both technical and non-technical stakeholders.
- Collaborate with analysts, coaches, and performance staff to understand requirements and translate them into actionable data solutions.
- Stay up to date with advancements in sports analytics, machine learning, and data science methodologies.
Your Background
- 3+ years of industry experience as a Data Scientist, plus a strong academic foundation.
- Python Data Science Stack: Advanced proficiency in Python, including Pandas, NumPy and scikit-learn.
- Statistical & Machine Learning Modelling: Experience with a variety of ML techniques (regression, classification, clustering, time-series forecasting). Experience with deep learning frameworks such as Keras or PyTorch.
- Model Deployment: Proven ability to productionise models, including building and deploying APIs.
- Strong visualization and communication skills, with the ability to translate complex technical findings into actionable insights for coaches, analysts, and execs.
Highly Desirable Skills
- Football Analytics Experience: Familiarity with football-specific datasets (event, tracking, positional), and libraries like mplsoccer.
- Advanced MLOps & Modelling: Experience with the Vertex AI ecosystem, especially pipelines, and advanced techniques such as player valuation, tactical modelling, etc.
- Bayesian Modelling: Knowledge of probabilistic programming (e.g., PyMC) for uncertainty-aware predictions.
- Stakeholder Collaboration: Demonstrated ability to work directly with stakeholders to scope, iterate, and deliver impactful solutions in fast-moving environments.
What They Offer
- A chance to work on real-world data that impacts elite football performance.
- Access to high-value datasets, sports science teams, and cross-disciplinary experts.
- A flexible hybrid working model (1 day per month in the London office).
- The opportunity to grow within a digital-first team at a world-renowned football club.
- The satisfaction of applying your engineering skills in an environment where your work directly influences results on the pitch.
Data Scientist (Football Club) in London employer: Singular Recruitment
Contact Detail:
Singular Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist (Football Club) in London
✨Tip Number 1
Network like a pro! Reach out to people in the football analytics space on LinkedIn or at industry events. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data models and visualisations related to football. This will give you an edge and demonstrate your passion for the sport.
✨Tip Number 3
Prepare for interviews by brushing up on your knowledge of football analytics and current trends in data science. Be ready to discuss how your work can impact decision-making in the club.
✨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 love seeing candidates who are proactive!
We think you need these skills to ace Data Scientist (Football Club) in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Scientist role. Highlight your experience with Python, machine learning, and any football analytics you've done. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for data science and football, and explain how you can contribute to our team. Keep it engaging and relevant to the role — we love creativity!
Showcase Your Projects: If you've worked on any relevant projects, make sure to mention them! Whether it's a personal project or something from your previous job, we want to see how you've applied your skills in real-world scenarios.
Apply Through Our Website: Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. We can't wait to see what you bring to the table!
How to prepare for a job interview at Singular Recruitment
✨Know Your Data Science Inside Out
Make sure you brush up on your Python skills, especially with libraries like Pandas and NumPy. Be ready to discuss your experience with statistical models and machine learning techniques, as well as how you've applied them in real-world scenarios, particularly in sports analytics.
✨Showcase Your Football Knowledge
Familiarise yourself with football-specific datasets and analytics. Being able to discuss how data impacts player performance and match outcomes will show your passion for the sport and your understanding of the role's requirements.
✨Prepare for Technical Questions
Expect to dive deep into technical discussions about model deployment and MLOps. Be prepared to explain how you've productionised models and built APIs, as well as any experience you have with advanced techniques like Bayesian modelling.
✨Communicate Clearly and Effectively
Practice translating complex data findings into simple insights. You’ll need to demonstrate your ability to communicate with both technical and non-technical stakeholders, so think of examples where you've successfully done this in the past.