AI/ML Data Science Engineer
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About this role
Location: South East London / Kent (hybrid - 3 days on-site)
Type: Permanent
Salary: Up to £88,000 + bonus
Sector: Global sports & entertainment / live event technology
A world-leading, globally recognised sports & entertainment organisation is hiring an AI/ML / Data Science Engineer to join its Innovation & Technology function. This role will design, build, and deploy intelligent data products and AI/ML solutions that support real-time operations, media/broadcast experiences, and digital fan engagement.
What you'll be doing
AI & Machine Learning
- Build and deploy ML models across:
- Predictive analytics (performance trends, forecasting)
- Computer vision (video analysis, media enhancement)
- NLP (fan insights, content intelligence, knowledge systems)
- Anomaly detection (telemetry/operations monitoring)
- Build scalable inference pipelines (real-time + batch)
- Implement monitoring, drift detection, and retraining workflows
- Prototype quickly to prove value, then scale into production
- Shape problem definitions with stakeholders in ambiguous environments
- Bring best practices from adjacent industries into a high-performance setting
Data Engineering & Architecture
- Design/maintain pipelines integrating telemetry/timing, video/image, event operations, and digital/commercial engagement data
- Develop APIs/services to expose analytics internally
- Ensure high availability and low latency where required
Cross-functional delivery
- Partner with Broadcast/Media, Operations, Commercial/Marketing, Cybersecurity/IT
- Communicate clearly to technical and exec audiences; become a trusted AI/data partner
Governance, compliance & security
- Responsible AI practices, privacy/governance support, and secure-by-design delivery with cyber teams
What we're looking for
Essentials
- 5-10 years' experience in data science / AI / ML engineering
- Strong Python
- Production ML deployment experience (end-to-end)
- Strong SQL + modern data warehouse experience
- Cloud familiarity + containerisation/orchestration
- Streaming data knowledge
- Solid stats/probability + evaluation + feature engineering
- Strong stakeholder communication + documentation; comfortable in event-driven environments
Desirable
- Real-time data environments; CV/video analytics; edge/low-latency; telemetry/IoT; sensor fusion; cybersecurity exposure
Company
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