Algorithm Researcher

Via Transportation · London, England ·

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Overview

In this role you design, develop, and scale Via’s core algorithms within production systems. You’ll bridge algorithm research, data science, and software engineering to solve real-world transit problems at scale. You’ll collaborate with cross-functional teams to turn research into reliable services that power global networks. This position offers hands-on impact in a fast-moving R&D environment, shaping the future of data-driven public mobility.

Pay / Benefits

  • equity
  • comprehensive health scheme
  • childcare salary exchange with YellowNest
  • Cycle to Work Scheme
  • office near Chancery Lane
  • weekly team lunches

Responsibilities

  • Design, develop, and improve core algorithms and business logic
  • Explore and evaluate algorithmic approaches using data and experiments
  • Develop and maintain mission-critical services for production deployment
  • Analyze large datasets to optimize algorithm performance
  • Own complex technical problems from research to production
  • Collaborate closely with algorithm developers, data scientists, and software engineers

Key requirements

  • 3+ years of relevant industry experience in algorithm development, data science, research, or software engineering with a strong algorithmic focus
  • Strong knowledge of algorithms, data structures, and analytical problem-solving
  • Strong Python skills and experience developing production-quality code
  • Experience applying data science, optimization, or analytical techniques to solve complex problems
  • Experience turning algorithms, models, or prototypes into production systems
  • Experience with DevOps and cloud infrastructure (Kubernetes) – strong advantage
  • Experience in architecture and maintaining cloud systems – strong advantage
  • Curious and analytical mindset; pragmatic, hands-on in bringing ideas to production
  • Curious and analytical
  • Pragmatic and problem-solver
  • Hands-on and production-focused
  • Python
  • production-quality code
  • data science
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