Kariera

Research Scientist (optimization)

Job Responsibilities:

  • Design, implement and maintain modules within our traffic simulator and software related to the operation of fleets of vehicles;
  • Designing solutions related to traffic models, vehicle routing, customer mode choice, capacitated charging, assignment with ride-sharing, multiple bin packing problems for vehicle loading and unloading (team work);
  • Guide junior engineers and software engineers to implement algorithms in real fleet management systems;
  • Interface with other teams (DevOps, simulation services, visualization services, etc);
  • Generate new ideas and contribute to the team’s vision and systems;

Education and Experience:

  • Ph.D. in Operations Research, Statistics, Applied Mathematics, Computer Science, Industrial and Systems Engineering or a related field with peer reviewed publications;
  • 7+ years of experience in numerical optimization of compute graphs;
  • 3+ years of software engineering experience in developing high-quality production software;

Core Skills:

  • Applicants should have expertise in data modeling and analysis, large-scale linear and integer programming, heuristic solutions design, and/or development of efficient optimization implementations;
  • A working knowledge of mathematical programming techniques (LPs, QPs, MIPs,..) accompanied by associated expertise in the use of tools and the latest technology for solving them (e.g. XPRESS, CPLEX, Gurobi, COIN-OR, etc.);
  • The ability to implement models and tools through the use of modeling languages (e.g. Python, R, Matlab) or more traditional languages (Java, C++);
  • Experience with statistical analysis;
  • Excellent communication skills;
  • Strong quantitative ability;
  • Analytical problem solving skills;
  • Desire to work in a fast-paced environment;

Preferred Skills:

  • Familiarity with logistics concepts – warehouse operations, forecasting, planning, optimization and logistics – gained through work experience or graduate level education;
  • Deep academic or industry expertise (post PhD 5+ years) in one or more related areas;
  • An active contributor to the relevant international research communities, and able to create and act as a champion of a specific sub-topic and particular technology or application;
  • Hands-on experience in applying optimization techniques to solve real-world transportation problems;
  • Experience in working with cloud platforms.

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