Senior Data Scientist, Personalisation

ERLPhase Power Technologies Ltd.

. Set the standard for recommender systems at Relay .

Posted 11/9/2026full-timeLondon • United KingdomSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and building scalable recommender systems, with a strong foundation in machine learning, operational research, and causal inference. Capable of leading projects from research to production while fostering collaboration and clear communication of complex ideas.

Highest-signal resume keywords

Recommender Systems DevelopmentReinforcement LearningMachine LearningOperational ResearchCausal Inference

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Recommender SystemsReinforcement LearningMachine LearningCausal InferenceLocation IntelligenceExperimentationData AnalysisOptimizationStatistical ModelingAlgorithm Development

Soft Skills

CollaborationCommunicationProblem-SolvingEntrepreneurial DriveAdaptability

Industry Keywords

Production SystemsResearch CultureTech CommunityCourier MatchingPersonalizationEvidence-Based Decision MakingPhysical-Network ConstraintsOpen-Ended ProblemsUK Visa Sponsorship

About the role

Key responsibilities & impact

Set the standard for recommender systems at Relay
Lead the evolution of Relay's recommender from research to production
Design and build recommender systems that power Relay's key decisions
Partner with Operational Research to unite recommender models and optimisation
Contribute to Relay's research culture and develop Relay's voice in the tech community
Build systems that match thousands of couriers to desired work while respecting physical-network constraints
Balance courier preferences, pricing, economics, personalisation, and optimisation
Work with machine learning, operational research, causal inference, location intelligence, and experimentation

Requirements

What you’ll need

Have built recommender systems at scale, owned them in production, and led their direction
Bring deep expertise in recommender systems, reinforcement learning and LLMs, whether from a PhD, publications, or years at the frontier in industry
Think in experiments, and let evidence guide decisions
Are energised by open-ended problems, and know how to make them tractable
Collaborate generously, and explain complex ideas simply
Strong technical fundamentals with entrepreneurial drive
Must answer whether UK visa sponsorship is needed now or in the future

Benefits

Comp & perks

Equal-opportunity employer committed to diversity, inclusion, and fostering a workplace where everyone thrives