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ERLPhase Power Technologies Ltd.

Quantitative Researcher, Optimisation

ERLPhase Power Technologies Ltd.

. Lead optimisation for Relay's last mile, making routing, pricing, and scheduling decisions for couriers and the wider network .

Posted 11/9/2026full-timeLondon • United KingdomMid-LevelSeniorWebsite

Core Competencies

Role fit
Core Competencies

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Demonstrates deep expertise in Operational Research and advanced quantitative disciplines, with a strong focus on building and optimizing systems that integrate Machine Learning and Recommender Systems. Proven ability to tackle complex problems and foster collaboration within a research-driven environment.

Highest-signal resume keywords
Operational Research ExpertiseOptimization Systems DevelopmentMachine Learning Model ProductionCollaboration and CommunicationEntrepreneurial Drive

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Operational ResearchOptimizationMachine LearningAlgorithm DevelopmentQuantitative AnalysisSolver DevelopmentData ModelingStatistical AnalysisProduction SystemsComplex Problem Solving
Soft Skills
CollaborationCommunicationProblem-SolvingGenerosity in TeamworkSimplifying Complex Ideas
Industry Keywords
Last-Mile DeliveryIndustrial EngineeringQuantitative DisciplineResearch CultureTechnology CommunityUK Visa Sponsorship

About the role

Key responsibilities & impact
  • Lead optimisation for Relay's last mile, making routing, pricing, and scheduling decisions for couriers and the wider network
  • Model and optimise decisions defining the last-mile delivery network and marketplace
  • Develop solvers and algorithms that perform live and at scale
  • Partner with Scientists to integrate ML and recommender systems with Operational Research
  • Raise the standard for Operational Research at Relay
  • Grow the team, research culture, and Relay's voice in the technology community

Requirements

What you’ll need
  • Deep expertise in operational research, whether from a PhD, publications, or years at the frontier in industry
  • Background in operational research, industrial engineering, or an advanced quantitative discipline, including trading, that has branched into optimisation
  • Experience building optimisation systems or ML models that run in production and owning the outcome
  • Ability to tackle large, messy problems and bring structure to them
  • Ability to collaborate generously and explain complex ideas simply
  • Strong technical fundamentals and entrepreneurial drive
  • UK visa sponsorship needs must be disclosed during application

Benefits

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