AI / ML Data Science Engineer

Job DescriptionLocation: South East London / Kent (hybrid - 3 days on-site )Type: PermanentSalary: Up to £88,000 + bonusSector: Global sports & entertainment / live event technologyA 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 doingAI & Machine LearningBuild 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 workflowsPrototype quickly to prove value, then scale into productionShape

problem definitions with stakeholders in ambiguous environmentsBring best practices from adjacent industries into a high-performance settingData Engineering & ArchitectureDesign/maintain pipelines integrating telemetry/timing, video/image, event operations, and digital/commercial engagement dataDevelop APIs/services to expose analytics internallyEnsure high availability and low latency where requiredCross-functional deliveryPartner with Broadcast/Media, Operations, Commercial/Marketing, Cybersecurity/ITCommunicate clearly to technical and exec audiences; become a trusted AI/data partnerGovernance, compliance & securityResponsible AI practices, privacy/governance support, and secure-by-design delivery with cyber teamsWhat we're looking forEssentials5-10 years' experience in data science / AI / ML engineeringStrong PythonProduction ML deployment experience (end-to-end)Strong SQL + modern data warehouse experienceCloud familiarity + containerisation/orchestrationStreaming data
knowledgeSolid stats/probability + evaluation + feature engineeringStrong stakeholder communication + documentation; comfortable in event-driven environmentsDesirableReal-time data environments; CV/video analytics; edge/low-latency; telemetry/IoT; sensor fusion; cybersecurity exposureTPBN1_UKTJ