Amazon
Manager, Research Science, Fulfillment Planning and Execution Science - Fulfillm
Amazon, Washington, District of Columbia, us, 20022
Manager, Research Science, Fulfillment Planning and Execution Science - Fulfillment Optimization
Job ID: 2753153 | Amazon.com Services LLCHave you ever wondered how Amazon predicts when your order will arrive and how we ensure that it actually arrives on the promised date/time? Have you wondered where all those Amazon semi-trucks on the road are headed? Are you passionate about increasing efficiency and reducing carbon footprint? If so, then we want to talk with you! At Amazon's Supply Chain Optimization Technologies (SCOT), we are tasked with optimizing the fulfilment of customer orders worldwide while ensuring Amazon customers get their orders on time.The Amazon Fulfillment Planning & Execution (FPX) Science team within SCOT - Fulfilment Optimization group is seeking a Manager of Research Science with expertise in Machine Learning and/or Optimization and a proven record of leading scientists and solving business problems through scalable ML solutions. FPX Science tackles some of the most mathematically complex challenges in transportation planning and execution to improve Amazon's operational efficiency worldwide.Your team and tech solution will have large impacts on the physical supply chain of Amazon and play a key role in improving Amazon consumer business’s long-term profitability. We’re looking for a passionate, results-oriented, and inventive Scientist who can lead from the front towards developing and deploying ML models for our outbound transportation planning systems.Key job responsibilities
As a Manager of Research Science within FPX Science team, you will lead a team of research and applied scientists towards designing and deploying solutions that draw from a range of scientific areas such as supervised, semi-supervised and unsupervised learning, reinforcement learning, advanced statistical modeling, and graph models. Responsibilities include:Lead a team of research and applied scientists towards design, development, and evaluation of highly innovative ML models for solving complex business problems.Technically lead and mentor the scientists on the team.Research and apply the latest ML techniques and best practices from both academia and industry.Use analytical techniques to create scalable solutions for business problems.Work closely with software engineering teams to build model implementations and integrate successful models and algorithms in production systems at very large scale.Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation, and model implementation.BASIC QUALIFICATIONS
- Ph.D. in Computer Science, Operations Research, Operations Management, Industrial Engineering, Statistics, Applied Mathematics, or a related field- 5+ years of hands-on experience in building machine learning models in a business environment- Proven track in leading and mentoring scientists with demonstrated ability to serve as a technical lead- Strong fundamentals in problem solving, algorithm design, and complexity analysis- Excellent communication skills, both written and oral catered appropriately towards both technical and business people.- Demonstrated ability to document models and analysis and present results/conclusions to influence business critical decisions.PREFERRED QUALIFICATIONS
- Experience leading a team of scientists across disciplines including RS, AS, DS- Prior well-established world-class recognized academic experience including multiple publications in top-tier academic journals; or industry experience conducting research in the aforementioned areas with proven track record in developing solutions for major business problems, demonstrating significant innovation, creativity, and judgment- Deep technical knowledge of machine learning and statistical methodologies- Prior experience modeling supply chain related problems- Experience of applying hybrid techniques in the space of ML and Operations Research is a big plus- Experience with fully automated machine training (e.g., automatic re-training, automatic testing)- Experience with high-impact decisions (>$1B)- 5+ years of production coding experience in one of the object-oriented programming languages such as Java, Python, C++, etc is a big plus.Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
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Job ID: 2753153 | Amazon.com Services LLCHave you ever wondered how Amazon predicts when your order will arrive and how we ensure that it actually arrives on the promised date/time? Have you wondered where all those Amazon semi-trucks on the road are headed? Are you passionate about increasing efficiency and reducing carbon footprint? If so, then we want to talk with you! At Amazon's Supply Chain Optimization Technologies (SCOT), we are tasked with optimizing the fulfilment of customer orders worldwide while ensuring Amazon customers get their orders on time.The Amazon Fulfillment Planning & Execution (FPX) Science team within SCOT - Fulfilment Optimization group is seeking a Manager of Research Science with expertise in Machine Learning and/or Optimization and a proven record of leading scientists and solving business problems through scalable ML solutions. FPX Science tackles some of the most mathematically complex challenges in transportation planning and execution to improve Amazon's operational efficiency worldwide.Your team and tech solution will have large impacts on the physical supply chain of Amazon and play a key role in improving Amazon consumer business’s long-term profitability. We’re looking for a passionate, results-oriented, and inventive Scientist who can lead from the front towards developing and deploying ML models for our outbound transportation planning systems.Key job responsibilities
As a Manager of Research Science within FPX Science team, you will lead a team of research and applied scientists towards designing and deploying solutions that draw from a range of scientific areas such as supervised, semi-supervised and unsupervised learning, reinforcement learning, advanced statistical modeling, and graph models. Responsibilities include:Lead a team of research and applied scientists towards design, development, and evaluation of highly innovative ML models for solving complex business problems.Technically lead and mentor the scientists on the team.Research and apply the latest ML techniques and best practices from both academia and industry.Use analytical techniques to create scalable solutions for business problems.Work closely with software engineering teams to build model implementations and integrate successful models and algorithms in production systems at very large scale.Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation, and model implementation.BASIC QUALIFICATIONS
- Ph.D. in Computer Science, Operations Research, Operations Management, Industrial Engineering, Statistics, Applied Mathematics, or a related field- 5+ years of hands-on experience in building machine learning models in a business environment- Proven track in leading and mentoring scientists with demonstrated ability to serve as a technical lead- Strong fundamentals in problem solving, algorithm design, and complexity analysis- Excellent communication skills, both written and oral catered appropriately towards both technical and business people.- Demonstrated ability to document models and analysis and present results/conclusions to influence business critical decisions.PREFERRED QUALIFICATIONS
- Experience leading a team of scientists across disciplines including RS, AS, DS- Prior well-established world-class recognized academic experience including multiple publications in top-tier academic journals; or industry experience conducting research in the aforementioned areas with proven track record in developing solutions for major business problems, demonstrating significant innovation, creativity, and judgment- Deep technical knowledge of machine learning and statistical methodologies- Prior experience modeling supply chain related problems- Experience of applying hybrid techniques in the space of ML and Operations Research is a big plus- Experience with fully automated machine training (e.g., automatic re-training, automatic testing)- Experience with high-impact decisions (>$1B)- 5+ years of production coding experience in one of the object-oriented programming languages such as Java, Python, C++, etc is a big plus.Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
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