Senior Data Scientist at Ludonautics
Job Description
Ludonautics is seeking an experienced Senior Data Scientist to join its growing sports advisory team, helping professional football clubs maximise their use of data to improve recruitment, squad building and sporting decision-making.
Founded by Ian Graham, Liverpool FC's former Director of Research, Ludonautics works with clubs to deliver world-class statistical analysis and data science consultancy. This is a unique opportunity to work alongside some of the industry's leading football analytics professionals while supporting clubs across the game.
Senior Data Scientist
As a Senior Data Scientist, you'll work directly with client clubs to understand their challenges, conduct bespoke football analysis, and provide evidence-based recommendations that influence recruitment strategy and sporting decisions.
The role combines advanced statistical modelling with football expertise, requiring someone who can identify meaningful questions, develop appropriate analytical approaches and clearly communicate insights to both technical and non-technical stakeholders.
You'll also help shape Ludonautics' evolving analytical models, tools and methodologies while building trusted relationships with club executives, sporting directors and recruitment teams.
- Deliver bespoke statistical analysis and football research for client clubs.
- Develop analytical models that support recruitment and squad planning.
- Analyse player and team performance to identify strengths, weaknesses and opportunities.
- Apply statistical modelling to solve complex football questions.
- Meet with client clubs to present findings and recommendations.
- Translate complex analytical outputs into clear, actionable insights.
- Support sporting directors and decision-makers with evidence-based advice.
- Travel to client clubs when required.
- Identify recurring client needs and improve internal analytical tools and models.
- Contribute to the ongoing development of Ludonautics' data science capabilities.
- Help evolve best practice within football analytics and consultancy.
Applicants should have:
- Extensive experience using Python.
- Strong SQL skills.
- Experience developing statistical models.
- Expertise in statistical data visualisation.
- Previous experience working within a professional football club.
- Excellent communication skills, with the ability to explain complex analysis to both technical and non-technical audiences.
- Strong analytical thinking, problem-solving ability and sound judgement.
The ideal candidate will be curious, commercially aware and passionate about using data to answer meaningful football questions that directly influence decision-making.
You'll thrive in this role if you:
- Have experience applying advanced analytics to real-world football problems.
- Understand player recruitment, squad building and football performance.
- Can balance technical excellence with practical decision-making.
- Enjoy collaborating with football clubs and senior stakeholders.
- Have a genuine curiosity about why things happen in football—not just what happened.
- Competitive salary.
- Fully remote working (UK-based).
- Flexible working hours.
- Holiday buyback scheme.
- Performance bonus linked to client and company success.
- Opportunity to work with one of football's most respected data science consultancies.
Founded in 2023 by Ian Graham, Ludonautics helps sporting organisations build stronger data science capabilities through innovative statistical analysis and consultancy. Ian led Liverpool FC's pioneering data science department between 2012 and 2023, helping establish one of football's most influential analytical operations.
Ludonautics prides itself on fostering a collaborative, supportive culture where data scientists are encouraged to challenge thinking, solve difficult problems and make a genuine impact across elite football.
This is an outstanding opportunity for an experienced football data scientist to work at the forefront of sports analytics, helping professional clubs make smarter, evidence-based decisions.
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