Seattle, Washington
INFORMS 2024
October 20 - 23, 2024
Seattle, Washington

Overview

Held each fall, the annual meeting brings together over 6,500 people to the world's largest operations research and analytics conference. It features more than 800 sessions and presentations, opportunities to meet with leading companies, universities and other exhibitors, an onsite career fair connecting top talent with over 100 organizations at the forefront of O.R. and analytics application, and other networking and educational events. The theme for the INFORMS Annual Meeting this year is “Smarter Decisions for a Better World” which encapsulates the core ethos of the organization and the mission it strives to achieve.

Amazon Science is a diamond sponsor of the INFORMS Annual Meeting this year and Fulfillment by Amazon (FBA) is a platinum sponsor of the INFORMS forum for Women in OR/MS (WORMS) this year.

Sponsorship Details

Amazon organizing committee

Workshops and tutorials

Modern Statistics in Social Media Analysis
October 21, 7:45 AM - 9:00 AM PDT
Data-Driven Supply Chain Optimization: Demand Forecasting and Deep Reinforcement
October 22, 10:25 AM - 11:00 AM PDT
Website: Link

Presenter: Sohrab Andaz
Measuring the Efficacy of Amazon’s Recommendation Systems
Unknown date

Work with us

US, WA, Bellevue
The Fulfillment by Amazon (FBA) and Supply Chain by Amazon (SCA) enable third-party sellers to use Amazon’s world-class science and logistics infrastructure to supply and fulfill customers world-wide with unprecedented fast delivery promise to customer. In doing so, sellers spend more time building great products, delight customers and grow their business. The FBA team is looking for a passionate, curious, and creative Principal Research Scientist with expertise in operations research, machine learning or statistics, along with a proven record of solving business problems through scalable modeling and analytical skills. As a lead research scientist in the team, you will be responsible for designing and implementing cutting edge optimization and ML models, building automated inventory, logistics and revenue management systems while collaborating with business and software teams to solve key challenges facing the worldwide FBA business. Such challenges include 1) designing end-to-end supply and demand management systems, ranging from capacity, inventory, and workforce management systems, 2) developing and improving optimization and ML models to help FBA sellers grow their business, 3) ensuring that worldwide Amazon customers have access to the largest selection of products through FBA sellers, and 4) driving out costs across end-to-end FBA supply chain. Unlike many companies who buy existing off-the-shelf planning systems, we design and build systems to suit Amazon’s particular needs. Our team members are on the forefront of supply chain thought leadership by working on some of the most difficult problems in the industry with some of the best product managers, research scientists, statisticians, economists and software developers in the business. We value individuals who exhibit deep technical proficiency, a desire for learning new areas, and a track record of delivering tangible results while fostering personal growth, team development, and career advancement. A day in the life In this pivotal role, you will be a technical leader in operations research or machine learning, with significant scope, impact, and visibility. Your solutions have the potential to drive billions of dollars in impact for Amazon's third-party seller business. As a senior scientist on the team, you will engage in every facet of the process—from idea generation, business analysis and scientific research to development and deployment of advanced models—granting you a profound sense of ownership. From day one, you will collaborate with experienced scientists, engineers, and product managers who are passionate about their work. Moreover, you will collaborate with Amazon's broader decision and research science community, enriching your perspective and mentoring fellow engineers and scientists. The successful candidate will have the strong expertise in applying operations research methodologies to address a wide variety of supply chain problems with millions of unique products involving hundreds of thousands of Selling Partners and tens of millions of customers worldwide. You will strive for simplicity, demonstrate judgment backed by mathematical rigor, as you continually seek opportunities to innovate, build, and deliver. Entrepreneurial spirit, adaptability to diverse roles, and agility in a fast-paced, high-energy, highly collaborative environment are essential. About the team Sellers play a vital role in Amazon’s ecosystem, integral to our mission of offering the Earth’s largest selection and lowest prices. FBA is a service that enables third-party sellers to outsource order fulfillment to Amazon, and leverage Amazon’s world-class facilities to provide customers Prime delivery promise. By partnering with Amazon, sellers benefit from powerful, cost-effective solutions that leverage our scale and technology, gain access to Prime members worldwide, increase their sales, and have more time to continue inventing amazing products for customers. With commitment to taking on even more of the supply chain and operational complexities on behalf of our selling partners, Amazon introduced Supply Chain by Amazon (SCA), an end-to-end, fully automated suite of supply chain services. This comprehensive solution empowers sellers to quickly and reliably transport products from manufacturing sites to customers worldwide. Amazon Warehousing and Distribution is a pivotal service in SCA, that provides best-in-class bulk storage and distribution services to sellers, ensuring they remain well-stocked across all their sale and fulfillment channels while reducing the total supply chain costs. The FBA team is the core group in charge of fulfillment, inventory management, pricing, and a diverse range of operational recommendation services for sellers, as well as building the internal resource management systems. We work to learn seller behavior, understand seller experience, build automated assistants to sellers, recommend right actions to sellers, design seller policies and incentives, and develop science products and services that empower third-party sellers to grow their businesses. To do so, we build and innovate science solutions at the intersection of machine learning, statistics, economics, operations research, and data analytics. We work full-stack, from foundational backend systems to future-forward user interfaces. Our culture is centered on rapid prototyping, rigorous experimentation, and data-driven decision-making.
US, WA, Bellevue
Amazon’s Modeling and Optimization (MOP) Team is looking for a passionate individual with strong optimization and analytical skills to join us in the endeavor of designing and improving the most complex transportation and fulfillment network in the world. The team is responsible for optimizing the global transportation and fulfillment network for Amazon.com and ensuring that the company is able to deliver our customers’ products to them as quickly, accurately, and cost effectively as possible. We design the network that delivers products from vendors and sellers to end customers, through both Amazon’s internal network as well as external partners, using multiple transportation modes. Optimizing the end-to-end network requires deep understanding of inventory management, placement, transportation, and supply chain management. Only through innovative and strategic thing, we will make the right capital investments in technology, buildings and equipment that allows for long-term success. Key job responsibilities We are seeking an experienced scientist who has a solid background in Operations Research, Supply Chain Management, Applied Mathematics, or other similar domain. In this role, you will develop and deploy models and tools that are innovative and scalable to solve new challenges in Amazon's global fulfillment network. You will collaborate with other scientists across teams to create integrated solutions that improves fulfillment speed, cost, and carbon emission. You have deep understanding of business challenges and provide scientific analysis to support business decision using a range of methodologies. You design science tool platforms, deploy models, create data pipelines, or simplify existing processes. About the team https://www.linkedin.com/feed/update/urn:li:activity:7089317294417346561/
US, WA, Seattle
Interested in helping build Prime's Machine Learning system to drive huge business impact on millions of customers? Join our team of Scientists developing algorithms to adaptively generate and experiment on new content, personalize, and optimize the Prime membership experience. This includes identifying building foundational models that serve as an abstraction of our high-dimensional customer data, understanding who our customers are, and providing them with personalized experiences. As an ML lead, you will partner directly with product owners to intake, build, and directly apply your modeling solutions. There are numerous scientific and technical challenges you will get to tackle in this role, such as deep learning techniques and natural language processing to abstract sequences and embeddings from customer features, offer/content features. These abstraction layers will then be used by our personalization, segmentation, and experimentation platforms. We employ techniques from deep learning, NLP, multi-armed bandits, optimization, and RL - while this role is focused on leading the cross-sectional space of deep learning, NLP, and RL. As the central science team within Prime, our expertise gets routinely called upon to weigh in on a variety of topics. We also emphasize the need and value of scientific research and have developed a strong publication and patent record (internally/externally) which you will be a part of. You will also utilize and be exposed to the latest in ML technologies and infrastructure: AWS technologies (EMR/Spark, Sagemaker, DynamoDB, S3, Andes, Bedrock ...), various ML algorithms and techniques (Random Forests, Neural Networks, supervised/unsupervised/semi-supervised/reinforcement learning, LLM's), and statistical modeling techniques. Major responsibilities: - Build and develop machine learning models and supporting infrastructure at TB scale, in coordination with software engineering teams. - Leverage Deep Learning, NLP, and Reinforcement Learning for our Optimization Systems. - Develop offline policy estimation tools and integrate with reporting systems. - Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation. - Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes. - Work closely with the business to understand their problem space, identify the opportunities and formulate the problems. - Use machine learning, data mining, statistical techniques and others to create actionable, meaningful, and scalable solutions for the business problems. - Design, develop and evaluate highly innovative models and statistical approaches to understand and predict customer behavior and to solve business problems.
US, WA, Seattle
Interested in helping build Prime's content and offer experimentation system to drive huge business impact on millions of customers? Join our team of Scientists and Engineers developing algorithms to adaptively generate and experiment on new content, personalize, and optimize the customer experience with Amazon Prime. This includes identifying who our customers are and providing them with personalized relevant content. As an ML lead, you will partner directly with product owners to intake, build, and directly apply your modeling solutions. There are numerous scientific and technical challenges you will get to tackle in this role, such as adaptive experimentation, structured multi-armed bandits and its application to various types of experimentation and multi-step optimization leading to reinforcement learning of the customer journey. We employ techniques from supervised learning, multi-armed bandits, optimization, and RL - while this role is focused on leading the space of multi-armed bandit solutions. As the central science team within Prime, our expertise gets routinely called upon to weigh in on a variety of topics. We also emphasize the need and value of scientific research and have developed a strong publication and patent record (internally/externally) which you will be a part of. You will also utilize and be exposed to the latest in ML technologies and infrastructure: AWS technologies (EMR/Spark, Redshift, Sagemaker, DynamoDB, S3, ...), various ML algorithms and techniques (Random Forests, Neural Networks, supervised/unsupervised/semi-supervised/reinforcement learning, LLM's), and statistical modeling techniques. Major responsibilities - Build and develop machine learning models and supporting infrastructure at TB scale, in coordination with software engineering teams. - Leverage Bandits and Reinforcement Learning for Experimentation and Optimization Systems. - Develop offline policy estimation tools and integrate with reporting systems. - Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation. - Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes. - Work closely with the business to understand their problem space, identify the opportunities and formulate the problems. - Use machine learning, data mining, statistical techniques and others to create actionable, meaningful, and scalable solutions for the business problems. - Design, develop and evaluate highly innovative models and statistical approaches to understand and predict customer behavior and to solve business problems.
US, WA, Bellevue
The Fulfillment by Amazon (FBA) and Supply Chain by Amazon (SCA) empower third-party sellers world-wide to use Amazon's cutting-edge logistics, warehousing, distribution, fulfillment, and transportation services. These services ensure products remain in stock, customer orders are fulfilled fast and reliably, while end-to-end supply chain costs are reduced. As a result, sellers can focus less on supply chain management and more on developing outstanding products, delighting customers, and scaling their businesses. The FBA team is looking for a passionate, curious, and creative Research Scientist with expertise in operations research, machine learning or statistics, preferably with a focus on pricing and market design, and a proven record of solving business problems through scalable modeling and analytical skills. As a research scientist in the team, you will be responsible for designing and implementing cutting edge optimization and ML models, building automated inventory, logistics, capacity and revenue management systems while collaborating with business and software teams to solve key challenges facing the worldwide FBA business. Such challenges include 1) designing end-to-end supply and demand management systems, 2) developing and improving optimization and ML models to support FBA sellers in growing their businesses, 3) creating decision-support tools that minimize the cognitive burden on sellers in navigating supply chain and operational complexities, 4) ensuring worldwide Amazon customers have access to the broadest selection of products from FBA sellers, and 5) driving cost efficiencies across end-to-end FBA supply chain. Unlike many companies that purchase off-the-shelf planning systems, we design and build custom solutions to suit Amazon's unique needs. Our team members are at the forefront of supply chain innovation, tackling some of the industry's most challenging problems alongside top product managers, research scientists, statisticians, economists, and software developers. We value individuals who exhibit deep technical proficiency, a desire for learning new areas, and a track record of delivering tangible results while fostering personal growth, team development, and career advancement. A day in the life As a scientist on the team, you will be involved with every aspect of the process—from idea generation, business analysis and scientific research to development and deployment of advanced models—granting you a profound sense of ownership. Your solutions have the potential to drive billions of dollars in impact for Amazon's third-party seller business. From day one, you will collaborate with experienced scientists, engineers, and product managers who are passionate about their work. Additionally, you will engage with Amazon's broader decision and research science community, enriching your perspective and mentoring fellow engineers and scientists. The ideal candidate will have the strong expertise in applying operations research methodologies to solve a wide variety of supply chain problems, involving millions of unique products, hundreds of thousands of Selling Partners, and tens of millions of customers worldwide. You will strive for simplicity and demonstrate judgment backed by mathematical rigor, as you continually seek opportunities to innovate, build, and deliver. An entrepreneurial spirit, adaptability to diverse roles, and agility in a fast-paced, high-energy, highly collaborative environment are essential. About the team Sellers are a crucial part of Amazon's ecosystem, playing an integral role in our mission to offer the Earth's largest selection and lowest prices. FBA is a service that enables third-party sellers to outsource order fulfillment to Amazon, and leverage Amazon’s world-class facilities to provide customers Prime delivery promise. By partnering with Amazon, sellers benefit from powerful, cost-effective solutions that leverage our scale and technology, gain access to Prime members worldwide, boost their sales, and free up time to focus on inventing amazing products for customers. To further ease supply chain and operational complexities for our selling partners, Amazon introduced Supply Chain by Amazon (SCA), an end-to-end, fully automated suite of supply chain services. With SCA, Amazon handles everything from picking up inventory from global manufacturing facilities, shipping across borders, managing customs clearance and ground transportation, to storing inventory in bulk, managing replenishment across Amazon and other sales channels, and delivering directly to customers— all without sellers having to worry about managing their supply chain. A pivotal service within SCA is Amazon Warehousing and Distribution, which offers best-in-class bulk storage and distribution services, ensuring sellers remain well-stocked across all their sales and fulfillment channels while reducing overall supply chain costs. The FBA team is at the heart of this operation, responsible for inventory management, automated replenishment, fulfillment, pricing, resource planning, capacity management, and a wide range of operational recommendation services for sellers. We focus on understanding seller behavior and experience, building automated tools and assistants, recommending optimal actions, designing seller policies and incentives, and developing science-driven products and services that empower third-party sellers to grow their businesses. We develop and innovate science-driven solutions at the intersection of machine learning, statistics, economics, operations research, and data analytics. Our work spans the full stack, from foundational backend systems to cutting-edge user interfaces. Our culture is rooted in rapid prototyping, rigorous experimentation, and data-driven decision-making.
JP, 13, Tokyo
The JP Economics team is a central science team working across a variety of topics in the JP Retail business and beyond. We work closely with JP business leaders to drive change at Amazon. We focus on solving long-term, ambiguous and challenging problems, while providing advisory support to help solve short-term business pain points. Key topics include pricing, product selection, delivery speed, profitability, and customer experience. We tackle these issues by building novel economic/econometric models, machine learning systems, and high-impact experiments which we integrate into business, financial, and system-level decision making. Our work is highly collaborative and we regularly partner with JP- EU- and US-based interdisciplinary teams. In this role, you will build production-grade machine learning models to serve best-in-class shopping and delivery experience to millions of customers on Amazon. This requires you to formulate ambiguous business problems into solvable scientific problems, work with large-scale data pipelines, perform extensive data cleaning and exploration, train and evaluate your models in a robust manner, design and conduct live experiments to validate model performance, and automate model inference on AWS infrastructure. The ideal candidate is an experienced data scientist or machine learning engineer who has built machine learning systems in production that delivers business impact at scale in a B2C industry. You are a self-starter who enjoys ambiguity in a fast-paced and ever-changing environment. You are extremely proficient in Python, SQL and distributed computing frameworks. You have excellent understanding of how machine learning models work under the hood. In addition, you may have worked with AWS infrastructure and causal uplift modeling techniques. You think big on the next game-changing opportunity but also dive deep into every detail that matters. You insist on the highest standards and are consistent in delivering results. We are open to consider high-potential candidates with less experiences for a more junior position. Key job responsibilities - Work with Product, Finance and Engineering to formulate business problems into scientific ones - Build large-scale data pipelines for training and evaluating the models using PySpark/SparkSQL - Extensively clean and explore the datasets - Train and evaluate ML models in a robust manner - Design and conduct live experiments to validate model performance - Automate model inference and monitoring and on AWS infrastructure
US, WA, Seattle
The Stores Economics and Science (SEAS) team uses Economics, Statistics, Operations Research and Machine Learning to understand and design the complex economy of Amazon’s network of buyers and sellers. We are an interdisciplinary team, committed to use of cutting edge technology and leveraging the strengths of engineers and scientists to build solutions for some of the toughest business problems at Amazon. We are looking for an outstanding Principal Applied Scientist who can invent novel approaches to previously unseen and intrinsically hard supply chain and logistics problems. We are looking for creative scientific experts who can combine a strong optimization toolbox with a desire to learn from others, and who know how to execute and deliver on big ideas. Experience in Operations Research, Optimization, Control Theory is essential, and you should be familiar with modern tools for data science and business analysis. Key job responsibilities This position requires drive and self-motivation, superior analytical thinking, data-driven disposition, application of technical knowledge to a business context, effective collaboration with fellow scientists, software development engineers, and product managers, effective communication of technical designs to technical and non-technical audiences, and close partnership with many stakeholders from operations, finance, IT, and business leadership. Key job responsibilities: - Seek to understand in depth the end to end eCommerce supply chain and identify areas of opportunities to grow our business using science solutions. - Apply state of the art optimization tools to intrinsically complex problems. - Contribute to the science strategy for SEAS Supply Chain and Logistics team. - Drive alignment across organizations to achieve business goals. - Lead/guide scientists and engineers across teams to develop, test, launch and improve of science models designed to optimize inventory value and customer experience. - Be responsible for communicating our innovations to the broader internal & external scientific community and business leadership. - Mentor and guide the applied scientists in our organization and hold us to a high standard of technical rigor and excellence in Operations Research.