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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 .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
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
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
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