Key Notes
Operations-research work focuses on dynamic pricing and bipartite matching for Wheely’s marketplace, from problem definition through production deployment. The role requires a master’s or PhD in an optimisation-focused field, mathematical programming, probability, statistics and Python. The London post pays £50,000–£70,000 and specifies four office days each week, with one remote day.
What You'll Work On
- Define ambiguous Pricing or Matching problems with Wheely engineers, data scientists, designers and product managers.
- Research and prototype machine-learning and optimisation models for dynamic pricing and bipartite marketplace matching.
- Deploy machine-learning and optimisation models into Wheely’s production systems.
- Improve existing marketplace algorithms and identify new opportunities for optimisation or machine-learning methods.
Why This Role Matters
- Wheely’s Pricing or Matching team takes optimisation models from research into production, connecting operations-research methods with dynamic-pricing or marketplace-matching decisions.
- Reviews of existing marketplace algorithms identify opportunities for improvement and new models, informing the team’s next research and development work on pricing or matching.
What They Are Looking For
- Qualification: A master’s degree or PhD in operations research, mathematics, management science or a closely related optimisation-focused field is required.
- Technical: A strong foundation in mathematical optimisation or mathematical programming is required.
- Domain: Probability, statistics, reinforcement learning and causal inference are required.
- Technical: Excellent Python programming and core machine-learning tools such as SQL and PyTorch are required.
- Preferred: Dynamic pricing, auction design or marketplace-matching exposure is advantageous; Q1/A* publications and conference participation are also preferred.