Job description
Who We Are
Founded in 1882, Tottenham Hotspur is an iconic football club, playing in the Premier League and Women’s Super League. From North London to the world, our fanbase spans continents, cultures, and generations. Spurs is a club that’s always dared to push boundaries, breaking new ground and rewriting history.
We offer world-class facilities: In 2019, we opened our state-of-the-art Stadium, a £1 billion landmark that’s the beating heart of North Tottenham’s transformation. More than just a football ground, it’s an engine of change — creating 4,000 jobs and injecting £300 million into the local economy every year.
We’re at our brightest when we’re all together. Our Club, our teams, our community.
There is only one Hotspur. Tottenham Hotspur.
Job Purpose
The Football Insights Department provides data-derived insights that impact decision-making across football departments, from the First Team to the Academy and including both Men’s and Women’s teams. Our mission is ensuring that critical processes, from player recruitment to performance optimisation, are consistently informed by thorough, high-quality information. With a focus on building a single source of truth, developing rigorous quantitative models, and delivering effective tools for interrogating data, our intention is to empower stakeholders with insightful statistical analyses that are both timely and actionable. Leveraging data as our fundamental commodity and powered by talent, we are looking to push the cutting edge of football analytics to drive the club towards its ambitious footballing vision.
The Club is seeking a senior data scientist to join the data science team.
As a Senior Data Scientist, you will play a key role in the data science team driving innovation and advanced analytics in football. Your focus will be on:
- Expanding our understanding of football through advanced modelling and analysis of tracking and event data.
- Developing and productionising predictive models to enhance match analysis, player performance evaluation, opponent analysis, and player identification.
- Collaborating with stakeholders across all squads (Men's, Women's Teams) to develop and deliver impactful insights.
- Driving the adoption of data-driven decision-making across football departments.
Key Responsibilities
Model Development:
- Work with tracking and event data to enhance understanding of match performance and tactical trends.
- Develop and maintain advanced statistical and machine learning models to generate meaningful insights from large football datasets.
- Apply innovative approaches to analysing team performance, match dynamics, and player performance.
- Ensure model outputs are interpretable and relevant for key stakeholders, including coaches, analysts, and scouts.
- Validate and refine models continuously to improve predictive accuracy and real-world application.
Model Deployment:
- Deploy models as self-service tools, ensuring insights are accessible and actionable.
- Ensure models and data solutions are robust, scalable, and well-integrated into existing club workflows.
- Collaborate with data engineers to improve model deployment efficiency and automation.
Collaboration & Communication:
- Work closely with technical and non-technical stakeholders to translate analytical outputs into football-relevant insights.
- Develop interactive dashboards and visualisations to communicate complex data in an intuitive way.
- Engage with cross-functional teams to ensure alignment of data science initiatives with football objectives.
Research & Innovation:
- Stay up to date with the latest research, methodologies, and tools in football analytics and machine learning.
- Experiment with emerging techniques to enhance the club's competitive advantage in data science.
- Promote a culture of continuous improvement and knowledge sharing within the data science team.
Personal Attributes
We are looking for a highly analytical and innovative thinker who can bridge technical expertise and football knowledge:
- Thinks ahead, generates innovative ideas.
- Respects others, builds relationships, collaborates.
- Delivers to the highest standards, takes responsibility.
- Works well in a fast-paced football environment.
Skills & Experience
Education & Background:
- Master’s or Ph.D. in a quantitative discipline such as Mathematics, Statistics, Computer Science, Data Science, or related fields.
- Experienced in data science, machine learning and football analytics.
Technical Skills:
- Strong experience with tracking data model development.
- Proficiency in Python and SQL for data analysis and model development.
- Strong experience handling large-scale datasets, including tracking and event-based data.
- Strong experience with statistical modelling, predictive analytics, and machine learning techniques.
- Ability to design, test, and validate models, ensuring reliability and robustness.
- Familiarity with cloud computing environments and model deployment best practices (Azure, Snowflake, dbt).
- Strong data visualisation and reporting skills to communicate insights effectively.
- Understanding of football data structures and how they can be leveraged for decision-making.
What sets this role apart?
- Work on cutting-edge data science solutions with direct impact on football performance and strategy.
- Develop and implement advanced analytics that shape the club’s decision-making process.
- Play a key role in innovating football data science within an elite performance environment.
Our values that bind us
DREAM THE IMPOSSIBLE – Impossible made possible when we think outside the box
DARE TO CHANGE THE GAME – Relentlessly strive for glory and leave our mark on the world
DO IT OUR WAY – Win the right way, never at all costs.
Our Responsibility to you
Safeguarding is fundamental to the success in all that we do. Successful candidates are to be reminded they would be subject to various background, DBS, and reference checks for this role.
We welcome applications from anyone regardless of age, disability, gender, race, or ethnic and national origins, religion or belief, or sexual orientation.
Note: This description excludes irrelevant sections and retains core responsibilities and qualifications.
