Senior Research Scientist

Description

Inventory Planning and Control (IPC) is seeking senior research scientists to join its New York science team. IPC owns Amazon's global inventory planning systems. We decide what, when, where, and how much we should buy to meet Amazon's business goals and to make our customers happy. We decide how to place and move inventory in Amazon network and what do with our current supply. We do this for hundreds of millions of items and hundreds of product lines worth billions of dollars of inventory world-wide. Our systems are built entirely in-house, and are on the cutting edge of automated large scale supply chain planning, optimization, execution and simulation technology. In IPC, we are simultaneously pushing the frontier of the science of supply chain planning for new and old business use-cases and solving some of the toughest computational challenges. We are responsible for studying, designing, and building systems to suit Amazon's needs and do not rely on existing off-the-self planning solutions. Our team members are on the forefront of supply chain thought leadership by working on the most challenging problems in the industry with some of the best minds in the business and academia.

The successful candidate has solid research experience in Operations Research preferably with focus on Operations Management or other closely related areas. He or she will lead the research where we are responsible for developing solutions to better manage and optimize worldwide inventory investments, while providing the best experience to our customers at the lowest possible cost through managing returns, liquidations and markdown processes. The research team is responsible for quantitative data analysis, building models and prototypes for supply chain systems, and developing state-of-the-art optimization algorithms that can scale for hundreds of millions of products. Scientists on the team closely collaborate with assortment planning, simulation and statistical testing platforms to jointly drive optimal decision making across different functions. This team plays a significant role in various stages of the innovation pipeline from identifying business needs, developing new algorithms, prototyping/simulation, to implementation by working closely with colleagues in engineering, product management, operations, retail and finance.

As a senior member of the research team, you will play an integral part in Amazon's inventory planning platform with the following technical and leadership responsibilities:

  • Interact with engineering, operations, science and business teams to develop an understanding and domain knowledge of processes, system structures, and business requirements
  • Apply domain knowledge and business judgment to identify opportunities and quantify the impact aligning research direction to business requirements and make the right judgment on research project prioritization
  • Develop scalable mathematical models to derive optimal or near-optimal solutions to existing and new inventory planning challenges
  • Create prototypes and simulations to test devised solutions
  • Advocate technical solutions to business stakeholders, engineering teams, as well as executive level decision makers
  • Work closely with engineers to integrate prototypes into production systems
  • Create policy evaluation methods to track the actual performance of devised solutions in production systems, identify areas with potential for improvement and work with internal teams to improve the solution with new features
  • Mentor team members for their career development and growth
  • Excel in evaluating the skill sets of candidates to make successful hiring decisions to meet business needs

Basic Qualifications

  • M.Sc. in Operations Research, Operations Management or a closely related field
  • More than 5 years of industrial and/or academic experience in supply chain management, inventory management, operations management, simulation or a closely related field
  • Ability to quantify improvement in business areas resulting from optimization techniques through use of business analytics and/or statistical modeling
  • Demonstrated use of modeling and mathematical optimization techniques tailored to meet real life problems through a record of achievements in industrial and/or academic environments
  • Excellent written and verbal communication skills with technical and business teams; ability to speak at a level appropriate for the audience. The ideal candidate can present business cases and document the models and analysis and present the results in order to influence important decisions

Preferred Qualifications

  • Ph.D. in Operations Research, Operations Management or a closely related field
  • In depth familiarity with the literature and practice of operations management, supply chain management, inventory management, revenue management, forecasting, and/or logistics
  • Prior well-established recognized academic experience, multiple publications in top-tier academic journals
  • Expertise in one of the following areas: Optimization, Applied Probability, Game Theory, and/or Simulation
  • Familiarity with Time Series Analysis and/or Predictive Modeling techniques
  • Demonstrated evidence of leading scientists as well as a record of developing junior members in industry and/or academic environments to a successful career track
  • Demonstrated experience to manage an industrial research team for three years or more
  • Experience with data engineering and/or methods used in Big Data analytics
  • Expertise in prototyping with applications of efficient large-scale data analysis in a complicated system
  • Prior work experience and/or academic research in area of online retail and competition with brick and mortar stores
  • Prior work experience and/or academic research in area of mechanism design and coordination/contracting within supply chains
  • Prior work experience and/or academic research in area of Pricing and Revenue Management

Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation


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