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The mission of the Surge team is to maintain overall marketplace reliability by balancing supply/demand in real-time through dynamic pricing. We build scalable real-time systems to understand the state of the market, forecast future demand, make predictions using ML models, solve network optimization programs, and eventually make pricing decisions for each rider session.
Job Responsibility:
Work with a mixed team of Engineers, Operations Researchers, and Economists
Build new scalable algorithms for real-time pricing of Ubers products across hundreds of global marketplaces
Take things from mathematical formulation through to prototype and experiment
Work with backend engineers to put your ideas into production
Requirements:
PhD in relevant fields (Operations Research, Industrial Engineering, Computer Science) with a focus on optimization modeling
Experience developing algorithms and models for large-scale optimization problems
Experience with optimization packages such as Gurobi, CPLEX, and OR Tools
Strong communication skills and ability to work effectively with cross-functional partners
Proficiency in one or more coding languages such as Python, Java, Go, or C++
Nice to have:
Experience with two-sided marketplace design, pricing optimization, matching/allocation, etc…
Familiarity with Machine Learning models, experimentation (e.g., A/B testing) and causal inference
What we offer:
Eligible to participate in Uber's bonus program
May be offered an equity award & other types of comp