Sr. Research Scientist
Amazon.com
Luxembourg, LU
il y a 6j

Amazon seeks motivated and innovative individuals with strong analytical skills and practical experience to join our Middle Mile Air and Ground Optimization team.

We are hiring specialists at all levels for our scientific team with expertise in transportation and systems engineering, network and combinatorial optimization, stochastic optimization, algorithm design, machine learning and demand forecasting.

Middle Mile Air and Ground transportation represents one of the fastest growing logistics areas within Amazon. Amazon Fulfillment Services transports millions of packages via air and ground and continues to grow year over year.

The scale of this operation challenges Amazon to design, build and operate robust transportation networks that minimize the overall operational cost while meeting all customer deadlines.

The Middle Mile Modeling and Optimization group is charged with developing an evolving suite of decision support and optimization tools to facilitate the design of efficient air and ground transport networks, optimize the flow of packages within the network to efficiently align network capacity and shipment demand, and effectively utilize scarce resources, such as aircraft and trucks.

Time horizons for these tools vary from years and months for long-term planning to hours and minutes for near-term operational decision making and disruption recovery.

These tools rely heavily on mathematical optimization, stochastic simulation, meta-heuristic and machine learning techniques.

In addition, Amazon often finds existing techniques do not effectively match our unique business needs which necessitates the innovation and development of new approaches and algorithms to find an adequate solution.

Amazon seeks motivated and innovative individuals with strong analytical skills and practical experience to join our Middle Mile Air and Ground Optimization team.

We are hiring specialists at all levels for our scientific team with expertise in transportation and systems engineering, network and combinatorial optimization, stochastic optimization, algorithm design, machine learning and demand forecasting.

Middle Mile Air and Ground transportation represents one of the fastest growing logistics areas within Amazon. Amazon Fulfillment Services transports millions of packages via air and ground and continues to grow year over year.

The scale of this operation challenges Amazon to design, build and operate robust transportation networks that minimize the overall operational cost while meeting all customer deadlines.

The Middle Mile Modeling and Optimization group is charged with developing an evolving suite of decision support and optimization tools to facilitate the design of efficient air and ground transport networks, optimize the flow of packages within the network to efficiently align network capacity and shipment demand, and effectively utilize scarce resources, such as aircraft and trucks.

Time horizons for these tools vary from years and months for long-term planning to hours and minutes for near-term operational decision making and disruption recovery.

These tools rely heavily on mathematical optimization, stochastic simulation, meta-heuristic and machine learning techniques.

In addition, Amazon often finds existing techniques do not effectively match our unique business needs which necessitates the innovation and development of new approaches and algorithms to find an adequate solution.

  • PhD in Operations Research, Applied Mathematics, Computer Science or related engineering fields, or equivalent experience.
  • Experience designing optimization solutions for very-large scale applications.
  • Detailed knowledge of optimization methods for solve large-scale linear and mixed-integer programming models.
  • Experience designing and implementing optimization models for discrete / combinatorial optimization problems (e.g., vehicle routing, scheduling, and facility location) and experience with leveraging such models to provide guidance for (long-
  • term) strategic and (Short-term) tactical decision making.

  • Excellent written and verbal communication skills with both technical, business, and operations people.
  • Strong problem-solving ability and the ability to work in ambiguous and constantly evolving environment.
  • Excellent communication skills with both technical and non-technical audiences
  • Ability to work independently and as part of a diverse team
  • 2+ years of experience
  • Deep understanding of MIP strategies to customize and leverage commercial algorithms and adapt them as required.
  • Deep understanding of decomposition methods and practical implementation experience.
  • Experience developing meta-heuristics algorithms for combinatorial optimization problems.
  • Strong programming skills and experience prototyping and developing software using standard programming languages (Java / C++).
  • Knowledge of tools for big data analytics (e.g. SQL, Python, Perl, or Ruby).
  • Project management experience working with tech and other cross-functional teams.
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