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Rugby AI Lead
Job in
Cardiff, Cardiff City Area, CF10, Wales, UK
Listed on 2026-10-18
Listing for:
Welsh Rugby Union (WRU)
Full Time
position Listed on 2026-10-18
Job specializations:
-
IT/Tech
AI Engineer (Applied/Software), Data Scientist, Machine Learning/ ML Engineer, AI Business & Operations
Job Description & How to Apply Below
- Degree, postgraduate qualification or equivalent professional expertise in data science, computer science, statistics, mathematics, artificial intelligence, machine learning or another relevant quantitative discipline.
- Strong practical experience applying data science, statistical modelling and machine learning to complex real-world problems.
- Advanced proficiency in Python and/or R, SQL and modern data-analysis and machine-learning environments.
- Degree, postgraduate qualification or equivalent professional expertise in data science, computer science, statistics, mathematics, artificial intelligence, machine learning or another relevant quantitative discipline.
- Strong practical experience applying data science, statistical modelling and machine learning to complex real-world problems.
- Advanced proficiency in Python and/or R, SQL and modern data-analysis and machine-learning environments.
- Demonstrable experience developing predictive models, including feature engineering, model selection, training, validation, tuning and ongoing performance monitoring.
- Strong understanding of statistical inference, uncertainty, hypothesis testing and the limitations of predictive models.
- Experience working with longitudinal, time-series or repeated-measures data and modelling change or progression over time.
- Practical understanding of modern generative AI and large language models, including their application to structured and unstructured information.
- Understanding of modern agentic AI architectures, including AI agents, tool use, retrieval, orchestration, workflow automation, multi-agent systems, memory and human-in-the-loop approaches.
- Ability to prototype and product ionise AI-enabled workflows rather than simply use off-the-shelf AI applications.
- Experience working with cloud-based data and AI environments and integrating models into scalable analytics products or operational workflows.
- Strong capability in data engineering fundamentals, including data wrangling, integration, quality assurance and working with complex and imperfect datasets.
- Ability to translate technically complex analysis into clear, actionable intelligence for non-technical decision-makers.
- Strong curiosity and experimentation mindset, with the ability to rapidly evaluate emerging technologies and distinguish genuine capability from hype.
- Ability to work effectively across disciplines, combining quantitative evidence with expert human judgement and contextual information.
- Strong understanding of responsible AI, including privacy, security, explainability, bias, model governance and appropriate human oversight.
- A growth mindset, commitment to continuous learning
- Ability to communicate and work through the medium of Welsh is desirable.
- Lead AI and data science across Talent Insight & Management, translating strategic rugby and talent questions into analytical models, AI capabilities and practical decision-support tools.
- Develop longitudinal player intelligence, connecting historical and current information across identification, pathway, professional and international rugby to understand how players develop over time.
- Build player trajectory and potential models using statistical modelling, machine learning, time-series and other appropriate techniques to understand changing trajectories, probability of progression and future international potential.
- Develop predictive indicators of future performance, exploring the interaction between technical, tactical, physical, behavioural, maturation, opportunity, exposure and contextual factors.
- Create an agentic AI workforce capable of securely undertaking appropriate elements of data gathering, research, monitoring, video and scouting workflows, player tracking, quality assurance, reporting and intelligence preparation for human review.
- Develop human-in-the-loop AI-enabled player intelligence systems, including automated player profiles, trajectory visualisations, alerts, comparison tools, depth-chart and succession modelling, that augment expert judgement and enable coaches and talent staff to interrogate evidence, understand uncertainty and make better-informed decisions.
- Integrate structured and unstructured information, including performance data, physical information, video, scouting observations, coaching assessments, reports and other relevant evidence to create a richer understanding of each player.
- Develop and product ionise advanced statistical and machine-learning models, ensuring models are appropriately validated,…
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