Sr. Research Scientist

2 months agoSeattle, WA


North America Sort Centers (NASC) Network Planning, Automation and is looking for Sr. Research Scientist.

Our team is working on mathematically complex challenges for Sort Center network planning to build state of the art network. We develop models to answer the questions on network design and connectivity, labor planning, volume and capacity planning to support our network long-term growth. Because we strive for faster delivery to customers a successful candidate must be passionate about identifying and building solutions that will help drive a more efficient network and lower cost of operations. You will lead the research where we are responsible for developing solutions to better manage and optimize network design, connectivity and planning. Our research and data science team is responsible for quantitative data analysis, building models and prototypes for network planning, and developing state-of-the-art algorithms that can scale for the whole network. In this role, you will develop scalable mathematical models to derive solution to existing network structure and create evaluation methods to track the performance and identify areas of improvements. The successful candidate has solid research experience in Operations Research preferably with focus on Operations Management or other closely related areas. In this role, you will partner with leadership, long-term and mid-term planning topology teams, senior operations managers, S&OP, , labor planning and finance teams, developing strategic and prediction solutions. The role will ensure that leadership is up to speed on important trends, tools and technologies and how they will be used to impact the business. Excellent business and communication skills are a must to develop and define key business questions and to build data sets that answer those questions. You should be able to work with business customers in understanding the business requirements and implementing reporting solutions.

• take ownership to define business problems, analyze and design solutions for complex problem areas and/or opportunities in existing or new business initiative; review model performance during implementation and identify opportunities for improvement.
• own the delivery of modelling solutions for an entire business application; define and prioritize science or engineering specifications for new approaches
• evaluate cross-team perspectives, use quantitative methods to derive justification, and build consensus on a roadmap on the required level of analyses to meet goal
• understand how easily a recommended solution can be implemented in a production software system and/or operational process.
• understand the various methods for capturing data from systems (e.g., logging, log harvesting, etc.) apply advanced science methods and principals, mathematical theory and/or statistical analysis to improve upon existing approaches. You work to resolve the root cause of endemic problems including areas where your team limits the innovation of other teams (bottlenecks).
• actively recruit and help others leverage your expertise, by participating in coaching and mentoring.


• PhD in Operations Research, Operations Management, Industrial Engineering, Statistics, Applied Mathematics or a related quantitative field
• 2+ years of experience in solving complicated problems in the area of Operations Management or similar disciplines developing strategies for networks.
• Ability to quantify improvement in business areas resulting from techniques through use of business analytics and/or statistical modeling
• Demonstrated use of modeling and mathematical 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 people; 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.
• Employer will accept a Master's degree or foreign equivalent in Operations Research, Operations Management, Industrial Engineering, Statistics, Applied Mathematics, or a related field and three years of research or work experience in the job offered or a related occupation as equivalent to the PhD and one year of experience.


• 7+ years of hands-on experience applying theoretical models in an applied environment
• Experience in and Chains
• Significant peer-reviewed scientific contributions in premier journals and conferences
• Proven ability to work effectively in a cross-functional team
• Ability to work on a diverse team or with a diverse range of coworkers
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