Data Scientist

Data Scientist

(one day a week in the central London office)

Sports Analytics

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