Garrett van Ryzin
Garrett van Ryzin joined Amazon's Supply Chain Optimization Technologies organization in August as a distinguished scientist.
Credit: Jesse Winter/Cornell University

How distinguished scientist Garrett van Ryzin is optimizing his time at Amazon

van Ryzin is focusing on driving innovations in areas ranging from inventory management to last-mile delivery.

Amazon announced in August 2020 that Garrett van Ryzin would be joining the company’s Supply Chain Optimization Technologies (SCOT) organization as a distinguished scientist. SCOT is responsible for designing, building, and operating the Amazon supply chain. SCOT systems manage inventory for the millions of items on Amazon, compute accurate delivery expectations for customer orders, and drive meaningful changes to Amazon’s fulfillment center network so that customers receive their packages in the most efficient way possible.

Prior to Amazon, van Ryzin was a professor of Operations, Technology and Information Management at Cornell Tech, and previously the Paul M. Montrone Professor of Decision, Risk, and Operations at the Columbia University Graduate School of Business.  His university research work has focused on algorithmic pricing, demand modeling, and stochastic optimization.

van Ryzin was also the head of marketplace optimization at ridesharing companies Lyft and Uber, where he led teams that developed models for a variety of functions, such as optimally dispatching drivers to riders, and developing pricing models and driver pay systems that improve market efficiency. Interestingly, van Ryzin’s paper that he wrote while pursuing his PhD at MIT “A Stochastic and Dynamic Vehicle Routing Problem in the Euclidean Plane” imagined a world of on-demand transportation as far back as 1991.

During his career, van Ryzin’s work on complex revenue management problems has enabled businesses across diverse industry sectors to get the most out of their limited capacity. To give just a few examples, van Ryzin’s research has enabled airlines to make a series of large-scale, dynamic and sequential decisions to determine the optimal price of a ticket at a particular moment in time. Retail companies have used similar dynamic optimization to manage inventory levels and prices for different products to maximize revenue.

What I find particularly interesting are problems that move beyond the constraints of optimizing within the system, to actually redesigning the system itself. 
Garrett van Ryzin

However, at Uber and Lyft van Ryzin tackled a new business environment, where revenue maximization wasn’t the primary goal. Instead, van Ryzin’s teams focused on optimizing more immediate metrics that were vital to the very survival of their services: service reliability, driver productivity, and growth.

For example, having a sufficient number of idle drivers at any given time is critical to maintaining throughput in ridesharing services. Surge pricing, a mechanism that van Ryzin’s team at Uber optimized, maintains an efficient level of idle drivers and encourages more drivers to get on the street during peak hours when they are needed the most.

van Ryzin sees technology-enabled service providers — be it at a ridesharing company like Lyft or the Fulfilled by Amazon (FBA) service — as transformational.  Only a few decades ago, businesses like these weren’t viable ways to organize service delivery due to high transaction costs and lack of real-time information. However, technology has radically improved information exchange and reduced transaction costs, which allows independent sellers to sell their products on Amazon much more efficiently than they could on their own.

In this interview, van Ryzin spoke about the different facets of market optimization, the intricacies of making automated decisions at scale, managing system complexity using approximation and decomposition ideas, and why he joined Amazon.

Q. What are the different elements of optimization?

I’d like to think of optimization being made up of human, technical and operational elements.

At a human level, the understanding of behavioral economics is absolutely critical. You have to create the right incentives for both suppliers and buyers to drive efficiencies. This is especially important for companies like Amazon that have many buyers and sellers participating and a high degree of decentralized activity. 

In addition to the human considerations, you also must develop a deep understanding of the technical elements of how these marketplaces work – the capabilities and limitation of the technology – which in turn allows you to gain insights into what structural changes are possible.

Finally, building services like Amazon that provide physical goods and services is a much more complicated endeavor than developing a service for trading virtual entities like stocks or mutual funds. To give just one example, at Amazon we are shipping actual, physical goods. This means the underlying physics of the infrastructure and the different operational elements are critical. So you must also think about your service in terms of factors like product weight and size, labor requirements, storage capacity, inventory levels, and lead times.

From a scientific perspective, there are several open questions in all three elements of market optimization. A fundamental one is determining the best approach to take to develop models to drive efficiency.

One approach is to develop structural models from first principles. For example, you could make an assumption that consumers are utility maximizers, develop a utility function and identify the parameters that constitute this utility function.

Garrett van Ryzin
Garrett van Ryzin, Amazon distinguished scientist

You could also take a radically different approach and build models based only on the underlying data – where you draw inferences from what the data alone tells you. Here, you’re not worrying about why something happened. Rather, you can use ideas from machine learning to estimate and refine predictive models without trying to understand the underlying mechanics.

What I find particularly interesting are problems that move beyond the constraints of optimizing within the system, to actually redesigning the system itself.  The ‘Wait and Save’ feature my group developed at Lyft is a good example. This product allows riders to opt into waiting for ten to fifteen minutes for a ride rather than having all rides be on-demand. In exchange for waiting, riders get a lower price. On the technology side, what we are doing here is actually changing the product in order to make the marketplace more efficient. I’ve always found there’s a lot more leverage in changing a system rather than optimizing within a fixed system.  It’s a lot trickier though because big structural changes often mean you have to get users comfortable with entirely new products or a completely new way of using the system.

Q. How do you account for the uncertainty and complexity inherent in large systems?

Approximation is at the heart of optimization because you can never fully represent the full complexity of a real-world trading system. For example, if a consumer places an order on Amazon, you have to make several sequential decisions with complex interactions.  Which fulfillment center should I take that order from? Should I place the items in the same box or should I pack them in different boxes? How will fulfilling this order impact the availability of inventory for the next order that comes in for that product? And how will it affect the available capacity of my local delivery assets?

You can develop approximation models by using a rolling horizon approach. This involves taking a best guess for what the future entails, and then updating your estimate for the future as and when you get new information. Or you could do something that’s far more sophisticated: build simulations of the future, and use sampling techniques to guide your decisions. You can also utilize reinforcement learning where you fit value functions to historical actions to arrive at decisions that are continually refined based on data.

Decomposition is also an important strategy for dealing with the interconnectedness of the different elements of the system. In large systems such as Amazon, everything is related to everything else. Supply affects costs, which affects pricing, which in turn affects demand, which affects dispatch, and so on. Ideally, you’d want to arrive at decisions by taking the whole system into account. However, the size of any real-world system makes this impossible. Any model you arrive at will be too complex, and you’d require a large amount of time to compute anything reasonable.

I’ve always been attracted to the idea of helping drive innovations to get people the basic, physical necessities that are essential to how they live.
Garrett van Ryzin

This is where decomposition comes in. You can break the system down into individual components – such as dispatch models, pricing models, inventory models and so on. The challenge here is to get these different models to collaborate. You don’t want scenarios where they are working at cross purposes with each other. For example, you don’t want one model trying to get rid of an item and have another model actively trying to replace it. In cases like these, you can drive coordination between different models using an internal price or some other mechanism that’s common to all the models.

These are just some of the trickiest issues in optimization, and I’m excited to be at Amazon where a lot of the innovation in these areas is taking place.

Q. Why did you decide to join Amazon?

I’ve always admired Amazon as a company because of its incredible track record of innovation across so many areas. I remember shopping at Amazon when they just sold books. And today, you have Amazon Studios, AWS, Amazon Devices, Alexa and even Project Kuiper where Amazon is putting up over 3,000 satellites in space.

Amazon is a company that excels at understanding economic opportunity and then building products and services that customers value. I’ve only been here for a few months, but I can already see how the company’s unique culture helps it be so successful across so many areas.

I also admire the company’s long-term perspective. Amazon doesn’t make decisions based on driving quarter-over-quarter performance. Amazon is willing to stick with ideas for many years. This appeals to me as a scientist as in my experience, sticking with the right idea over the long term is essential to making fundamental breakthroughs.

At SCOT, I’m excited to have the opportunity to contribute across so many areas, from FBA to last-mile delivery. Over the last few months, Amazon has helped so many people across the world get essential items during the pandemic. I’ve always been attracted to the idea of helping drive innovations to get people the basic, physical necessities that are essential to how they live.


View from space of a connected network around planet Earth representing the Internet of Things.
Get more from Amazon Science
Sign up for our monthly newsletter

Work with us

See more jobs
US, CA, Milpitas
We are a passionate team of doers that apply cutting-edge advances in technology to solve real-world problems and transform our customers’ experiences in ways we can’t even imagine yet. As an Applied Scientist, you will be working with a unique and gifted team developing exciting products for customers and collaborating with cross-functional teams.Responsibilities· Collaborate across functions to , develop and implement algorithms to solve high-impact problems· Evaluate statistical modeling and Machine Learning approaches using historical data· Define requirements and measurement criteria for scientific and machine learning models.· Translate model prototypes into secure, stable, testable, and maintainable production services.· Develop automated approaches towards monitoring model performance and evaluating impact.· Encourage and support knowledge-sharing within team and external groups· Responsible for influencing technical decisions in areas of /modelling that you identify as critical future offerings· Deliver algorithm and ML projects from beginning to end, including understanding the customer needs, aggregating data, exploring data, building & validating predictive models, and deploying completed models.Amazon is looking for an Applied Scientist to join an exciting new project team working to build a completely new, best in class . Our team is fast paced, highly collaborative and is organized like a startup.Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.Our main office is Milpitas Ca but other US-based Amazon centers are ok.
US, VA, Arlington
Are you seeking an environment where you can drive innovation? Do you want to apply machine learning techniques and advanced statistical modeling to solve real world problems to help Amazon reach and delight millions of customers around the world? Do you want to play a crucial role in the future of Amazon?Every time an Amazon customer makes an order they leverage the most advanced and sophisticated supply chain the world has ever seen, Amazon, and its global network comprising of cutting edge software, fulfillment centers, sort centers, delivery stations, airports, customer service centers, physical stores, robots, airplanes, trucks, vans, trucks, world class employees, trusted partners, and more. Conducting a symphony of this scale comes with significant costs.Here in WW Consumer Finance, our data scientists raise the bar on our ability to fulfill promises to customers at greater convenience, speed, and value through:· Developing visual solutions which help Amazonians search, find, compare, and buy goods / services critical to Amazon's operations· Developing production-ready machine learning solutions to drive savings across Amazon's corporate procurement catalog· Working with technical and non-technical customers across every step of data science project life cycle.· Collaborating with our dedicated product, data engineering, and software development teams to create production implementations for large-scale data analysis.· Developing an understanding of key business metrics / KPIs and providing clear, compelling analysis that shapes the direction of our business.· Presenting research results to our internal research community.· Leading training and informational sessions on our science and capabilities.Your contributions will be seen and recognized broadly within Amazon, potentially contributing to the Amazon research corpus and patent portfolio.
US, VA, Arlington
Are you seeking an environment where you can drive innovation? Do you want to apply machine learning techniques and advanced statistical modeling to solve real world problems to help Amazon reach and delight millions of customers around the world? Do you want to play a crucial role in the future of Amazon?Every time an Amazon customer makes an order they leverage the most advanced and sophisticated supply chain the world has ever seen, Amazon, and its global network comprising of cutting edge software, fulfillment centers, sort centers, delivery stations, airports, customer service centers, physical stores, robots, airplanes, trucks, vans, trucks, world class employees, trusted partners, and more. Conducting a symphony of this scale comes with significant costs.Here in WW Consumer Finance, our quantitative researchers raise the bar on our ability to fulfill promises to customers at greater convenience, speed, and value through:· Developing models to support the identification of investment opportunities consistent with Amazon strategic priorities· Developing models identifying synergy opportunities and risks in potential transactions· Serving as a subject matter expert on investment lead pipeline and valuation methodologies· Establish the ongoing processes, skill sets, and strategy that will enable Amazon to continue to build out our financial engineering competency, in the face of extremely fast growth and a rapidly changing industry· Working with technical and non-technical customers across every step of data science project life cycle.· Collaborating with our dedicated product, data engineering, and software development teams to create production implementations for large-scale data analysis.· Developing an understanding of key business metrics / KPIs and providing clear, compelling analysis that shapes the direction of our business.· Presenting research results to our internal research community.· Leading training and informational sessions on our science and capabilities.Your contributions will be seen and recognized broadly within Amazon, potentially contributing to the Amazon research corpus and patent portfolio.
US, VA, Arlington
Are you seeking an environment where you can drive innovation? Do you want to apply machine learning techniques and advanced statistical modeling to solve real world problems to help Amazon reach and delight millions of customers around the world? Do you want to play a crucial role in the future of Amazon?Every time an Amazon customer makes an order they leverage the most advanced and sophisticated supply chain the world has ever seen, Amazon, and its global network comprising of cutting edge software, fulfillment centers, sort centers, delivery stations, airports, customer service centers, physical stores, robots, airplanes, trucks, vans, trucks, world class employees, trusted partners, and more. Conducting a symphony of this scale comes with significant costs.Here in WW Consumer Finance, our applied scientists raise the bar on our ability to fulfill promises to customers at greater convenience, speed, and value through:· Developing production ready solutions which help Amazonians search, find, compare, and buy goods / services critical to Amazon's operations· Developing production-ready machine learning solutions to improve Amazon's corporate procurement catalog· Working with technical and non-technical customers across every step of data science project life cycle.· Collaborating with our dedicated product, data engineering, and software development teams to create production implementations for large-scale data analysis.· Developing an understanding of key business metrics / KPIs and providing clear, compelling analysis that shapes the direction of our business.· Presenting research results to our internal research community.· Leading training and informational sessions on our science and capabilities.Your contributions will be seen and recognized broadly within Amazon, potentially contributing to the Amazon research corpus and patent portfolio.
US, VA, Arlington
Are you seeking an environment where you can drive innovation? Do you want to apply machine learning techniques and advanced statistical modeling to solve real world problems to help Amazon reach and delight millions of customers around the world? Do you want to play a crucial role in the future of Amazon?Every time an Amazon customer makes an order they leverage the most advanced and sophisticated supply chain the world has ever seen, Amazon, and its global network comprising of cutting edge software, fulfillment centers, sort centers, delivery stations, airports, customer service centers, physical stores, robots, airplanes, trucks, vans, trucks, world class employees, trusted partners, and more. Conducting a symphony of this scale comes with significant costs.Here in WW Consumer Finance our applied scientists raise the bar on our ability to fulfill promises to customers at greater convenience, speed, and value through:· Developing production ready solutions which help Amazonians search, find, compare, and buy goods / services critical to Amazon's operations· Developing production-ready machine learning solutions to improve Amazon's corporate procurement catalog· Working with technical and non-technical customers across every step of data science project life cycle.· Collaborating with our dedicated product, data engineering, and software development teams to create production implementations for large-scale data analysis.· Developing an understanding of key business metrics / KPIs and providing clear, compelling analysis that shapes the direction of our business.· Presenting research results to our internal research community.· Leading training and informational sessions on our science and capabilities.Your contributions will be seen and recognized broadly within Amazon, potentially contributing to the Amazon research corpus and patent portfolio.
US, WA, Seattle
We are constantly making Alexa the best voice assistant in the world. Amazon’s Alexa cloud service and Echo devices are used every day, by people you know, in and about their homes. The Alexa Monetization team is hiring talented and experienced Sr. Applied Scientists to help building the next generation products for Alexa across multiple channels and domains. We are seeking an experienced, entrepreneurial, big thinker for a confidential new initiative within Alexa. You will be joining a team doing innovative work, making a direct impact to customers, showing measurable success, and building with the latest natural language processing systems. If you are holding out for an opportunity to:Make a huge impact as an individual· Be part of a team of smart and passionate professionals who will challenge you to grow every day· Solve difficult challenges using your expertise in coding elegant and practical solutions· Create applications at a massive scale used by millions of people· Work with machine learning systems to deliver real experiences, not just researchAnd you are experienced with…· Drive applied science (machine learning) projects end-to-end ~ from ideation, analysis, prototyping, development, metrics, and monitoring· Conduct deep analyses on massive user and contextual data sets· Propose viable modeling ideas to advance optimization or efficiency, with supporting argument, data, or, preferably, preliminary results· Design, develop, and maintain scalable, Machine Learning models with automated training, validation, monitoring and reporting· Stay familiar with the field and apply state-of-the-art Machine Learning techniques to NLP and related optimization problems· Produce peer-reviewed scientific paper in top journals and conferencesAnd you constantly look for opportunities to…· Innovate, simplify, reduce waste, and increase efficiencies· Use data to make decisions and validate assumptions· Automate processes otherwise performed by humans· Learn from others and help grow those around you...then we would love to chat!In 2021, we have the opportunity to build new products and features from the ground up and we are looking for strong, bias for action engineering leaders who are not afraid of taking bold bets and trying new things to improve customer experience for Alexa.As part of a new and growing team, you will be iterating on new features and products to help drive innovation and expansion. You will work on cross-functional and cross-domain opportunities; tackle challenging projects aim to accelerate experimentations in Alexa; and build out operating mechanisms and technology to enable novel customer experiences. You will be instrumental in setting the team culture, quality bar, engineering best practices, and norms. Mentoring and growing the team around you will be one of the primary ways you measure your own success. You will have the opportunity to contribute and develop deep expertise in the areas of distributed systems, machine learning, conversational technologies, user interfaces (including voice and natural user interfaces), data storage and data pipelines.This role is exciting for scientists who love to apply startup mindset to their day-to-day, enjoy working cross-functionally to master both business and technology knowledge, and are passionate about building engineering best practices. If you are looking for opportunity to learn, grow and lead, this is the position for you.
IN, KA, Bengaluru
Do you want to join an innovative team of scientists who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon’s customers? Do you want to build and deploy advanced algorithmic systems that help optimize millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data to solve real world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Machine Learning and Data Sciences team for India Consumer Businesses.If you have an entrepreneurial spirit, know how to deliver, love to work with data, are deeply technical, highly innovative and long for the opportunity to build solutions to challenging problems that directly impact the company's bottom-line, we want to talk to you.Major responsibilities· · Use machine learning and analytical techniques to create scalable solutions for business problems· · Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes· · Design, development, evaluate and deploy innovative and highly scalable models for predictive learning· · Research and implement novel machine learning and statistical approaches· · Work closely with software engineering teams to drive real-time model implementations and new feature creations· · Work closely with business owners and operations staff to optimize various business operations· · Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation· · Mentor other scientists and engineers in the use of ML techniques
US, CA, San Diego
.A day in the life.About the hiring group.Job responsibilitiesEconomistThe North American Consumer Economics team uses Economics, Statistics, 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 Economist who is able to provide structure around complex business problems, work with machine learning scientists to estimate and validate their models on large scale data, and who can help business and tech partners turn the results of their analysis into policies, programs, and actions that have a major impact on Amazon’s business. We are looking for creative thinkers who can combine a strong economic toolbox with a desire to learn from others, and who know how to execute and deliver on big ideas.In this role, we expect you be able to own the development of economic models and to manage, in close collaboration with scientists and engineers, the data analysis, modeling, and experimentation that is necessary for estimating and validating your model. You will need to work with our business partners to communicate the properties of your analysis/modeling and be able to work to incorporate their feedback and requests into your project. Experience in applied economic analysis is essential, and you should be familiar with modern tools for data science and business analysis.We are particularly interested in candidates with research background in applied microeconomics, empirical IO, Marketing, Finance, applied econometrics, and market design. However, we want to talk with any experienced economist with an interest in working on an interest in working on innovative, strategic problems with significant business impact.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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
CA, BC, Vancouver
Are you passionate about driving business & customer impact through thoughtful analysis and data-driven insights? Are you a deeply technical individual who enjoys working with customers to transform how a business operates? Are you a builder that excels with ambiguity? Are you inspired by invention? Is problem solving through teamwork and working in a startup environment in your DNA? Do you like the idea of seeing how your work impacts the bigger picture?Answer yes to any of these and you’ll fit right in here.We are looking for Data Scientist professionals to drive our analytical revolution in the Talent Acquisition (TA) space. You get the opportunity to work on a ground up rebuild of our analytical capabilities, from data ingress, to complex business transformations to end user reporting and beyond. In this role, you will invent and build on behalf of candidates, experiment and test new ideas, evangelize successes, and drive consistency.The ideal candidate is an independent Data Scientist who can source data, cleanse, analyze, refine, enrich, model, present, automate and document our business data pipelines. You will always be on the lookout for ways to optimize the information flow process, stay on top of latest trends in data warehousing and be able to coordinate and work on multiple, related projects.Responsibilities:· Collaborate with recruiting operations, data scientists, and business leaders to define business processes and provide analytical support· Leverage code to analyze complex datasets and design, develop and evaluate data transformations to solve specific business problems· Build scalable, efficient, and automated data processes to facilitate customer-facing reporting· Automate TA processes to streamline business operations· Communicate verbally or in writing to business customers / leadership to sharing insights and recommendationsThis role can be based out of any US/Canada AWS Corporate location (i.e. Seattle, WA, Arlington, VA, Herndon, VA, New York, NY, Boston, MA, Chicago, IL, Dallas, TX, Cupertino, CA, Palo Alto, CA).
LU, Luxembourg
At Amazon, we strive to be the most innovative and customer centric company on the planet. Come work with us to develop innovative Customer Fulfilment products, tools and research driven solutions in a fast-paced environment by collaborating with smart and passionate leaders, program managers, data scientists and software developers. Our mission is to build the most efficient, intelligent and interpretable solutions on the planet.The EU Ops Integration Analytics team is part of Amazon EU Customer Fulfillment and is responsible for improving and supporting performance management of our Fulfilment Centers through state-of-the-art and scalable analytics solutions. We work backwards from the customer and define new innovative solutions that raise the bar on customer experience whilst constantly lowering our cost and supporting our continued growth.We are looking for a thought leader and you demonstrate this by delivering solutions, not just by having ideas. We encourage you to shape the business with data driven recommendations. A successful candidate has an entrepreneurial spirit and wants to make a big impact. You will develop strong working relationships and thrive in a collaborative team environment. Your role requires the ability to influence and interact with broad range of stakeholders (technical and non-technical). You draw from a broad data science expertise to mentor Data Scientists and Business Intelligence Engineers; following a rigorous scientific methodology, while providing leadership on complex analytical topics. You provide guidance on cutting-edge methods in big data processing, data science literature, experimentation and careful consideration of modeling decisions. We expect you to have breadth of data science knowledge, and depth in predictive modeling (supervised learning) and unsupervised learning (clustering).Key Responsibilities· Develop predictive models and decision science to guide program and operations teams on improving our customer experience (e.g. predicting concessions and optimizing the best action to take, sustainability and energy etc.)· Drive data science best practices and mentoring junior team members based on your in-depth knowledge in theoretical and practical data science disciplines.· Proactively seek to identify business opportunities and provide solutions based on a broad and deep knowledge of Amazon’s data resources, industry best-practices, and work done by other teams.· Partner with, coordinate, and influence multiple teams outside of EU Customer Fulfillment (Customer Service, Transportation, Amazon Logistics.), to support key initiatives.· Be the voice of the customer (end customer and data consumer), aligning stakeholders with scalable mechanisms to incorporate our models into product and engineering decision-making processes.· Drive and promote experimentation culture (e.g. A/B testing) with data-driven mindset and measurable approach.
GB, London
Come build the future of entertainment with us. Are you interested in shaping the future of movies and television? Do you want to define the next generation of how and what Amazon customers are watching?Prime Video is a premium streaming service that offers customers a vast collection of TV shows and movies - all with the ease of finding what they love to watch in one place. We offer customers thousands of popular movies and TV shows from Originals and Exclusive content to exciting live sports events. We also offer our members the opportunity to subscribe to add-on channels which they can cancel at anytime and to rent or buy new release movies and TV box sets on the Prime Video Store. Prime Video is a fast-paced, growth business - available in over 240 countries and territories worldwide. The team works in a dynamic environment where innovating on behalf of our customers is at the heart of everything we do. If this sounds exciting to you, please read on.The Research & Insight team operates in a dynamic and entrepreneurial environment across Europe and the world to understand our customers holistically. We work with senior stakeholders across a wide range of functions to plan, execute, and deliver continuous knowledge and insight to marketing and business teams to deliver customer centric growth.We are looking for a Sr. Data Scientist, Market Research to build our data strategy from the ground up. In this role, you will define quantitative research data standards and structures for end-to-end research processes, ensuring fit for purpose databases that are widely accessible and in usable formats for a variety of stakeholders. You will architect tools such as dashboards and automated reporting to help democratize our market research data. You’ll leverage predictive models, advanced machine learning/AI capabilities and exploratory data analysis (EDA) to solve problems and deliver insight.Responsibilities· Collecting and structuring data from a variety of 3P agency partners and APIs.· Collaborate closely with research, marketing, finance and content partner teams to ensure your data roadmap is fit for purpose across stakeholder groups.· Define and develop data management platforms, analysis tools and user friendly dashboards and reports.· Conduct ad-hoc analysis and predictive modelling to extract value from data to uncover opportunities and recommend actions.· Visualize data sets to inspire stakeholders (word clouds, infographics).· Perform regular data and system audits and feedback to ensure complete, accurate and usable data.· Optimize self-serve platform for data reporting and analysis to accelerate information-to-action at scale.· Build capability training across data and tools.· An SME for research data platform tools and analysis capabilities and delivery.
US, WA, Seattle
Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products.Worldwide Ad Success team (WASE) is at the forefront of our amazing growth machine enabling our teams to deliver at scale. Our goal is to scale account management multifold by investing in strategic self-service applications that improve productivity of external advertising customers and internal account management executives. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities.As part of our team evolution we are investing in improving our understanding of the advertisers on Amazon through advanced ML modeling and building an ML service that delivers recommendations to advertisers and solves the prioritization and selection of most optimum recommendations and measure impact with explain-ability.We are moving fast and have the ability to shape our tech infrastructure that will combine science and scalable engineering at a rapid pace. We are looking for a senior Applied Scientist to join the team to drive key science methods and delivery of the project, working closely with product and engineering leads, as well as our leadership. This is a relatively new team, with a focused initiative. We’re a fast-growing team with high visibility from the leadership team and lots of new opportunities.As an Applied Scientist on this team you will:· Solve business problems using state of the art machine learning methods.· Work on full life-cycle projects - from researching the optimal machine learning models to use to deploying your models into production.· Drive processes, tools, and statistical methods that support rational decision-making.· Be technically fearless: You aren't satisfied by performing 'as expected' and push the tech teams past conventional boundaries. Your dial goes to '11'.· Help grow recruit other scientists to achieve outstanding results.· Foster a creative atmosphere to let engineers and other PMs innovate, while holding them accountable for making smart decisions and delivering results.· Explore new problem spaces with unique constraints and thus non-obvious solutions; identify any gaps in the solutions and/or approach.Why you love this opportunityAmazon is investing heavily in building a world-class advertising business. We are responsible for defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long-term growth. We deliver billions of ad impressions and millions of clicks daily and break fresh ground to create world-class products. We are highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit. With a broad mandate to experiment and innovate.Impact and Career GrowthYou will invent new shopper and advertiser experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon. Define a long-term science vision for our advertising business, driven fundamentally from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding.Team video https://youtu.be/zD_6Lzw8raEAmazon 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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us
US, VA, Arlington
Amazon Global Talent Management (GTM) Science is an innovative organization that exists to propel Amazon HR towards being the most scientific HR organization on earth. The GTM Science mission is to use Science to assist and measurably improve every talent decision made at Amazon. We do this by discovering signals in workforce data, deploying statistical models into Amazon’s talent products, and guiding the broader GTM team to pursue high-impact opportunities with tangible returns. This multi-disciplinary approach spans capabilities, including: data engineering, reporting and analytics, research and behavioral sciences, and applied sciences such as economics and machine learning.We are seeking a Senior Research Scientist with deep quantitative and qualitative research expertise in Diversity, Equity, and Inclusion (DEI) and the Future of Work (FoW). This person will possess a strong mixed methods background, knowledge of different approaches to evaluating fairness in employment decisions, and experience with analyzing DEI data. In this role you will:· Design, develop, and execute quantitative and qualitative data collection methods in future of work, DEI, and related talent management efforts· Conduct quantitative analyses of DEI data and trends· Conduct qualitative data collection and analysis· Partner closely with Amazon Global DEI teams· Partner closely and drive effective collaborations across multi-disciplinary research and product teams· Manage full life cycle of large scale research programs related to DEI
US, CA, East Palo Alto
MULTIPLE POSITIONS AVAILABLEEntity: Amazon Web Services, Inc., an Amazon.com CompanyTitle: Applied Scientist IILocation: East Palo Alto, CAPosition Responsibilities:Participate in the design, development, evaluation, deployment and updating of data-driven models and analytical solutions for machine learning (ML) and/or natural language (NL) applications. Develop and/or apply statistical modeling techniques (e.g. Bayesian models and deep neural networks), optimization methods, and other ML techniques to different applications in business and engineering. Routinely build and deploy ML models on available data. Research and implement novel ML and statistical approaches to add value to the business. Mentor junior engineers and scientists.Amazon.com is an Equal Opportunity-Affirmative Action Employer - Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.#0000
US, WA, Seattle
We are a passionate team working to build a best-in-class healthcare product designed to make high-quality healthcare easy to access.We are looking for a truly innovative and technically strong applies scientist with a background in machine learning and natural language understanding.As a Senior Applied Scientist, you will:· develop models for various natural language processing tasks, including named-entity recognition, natural language inference, sentiment analysis, text summarization, and question answering within in a healthcare context· work closely with product managers to expand the depth of our product insights with data, create a variety of experiments, and determine the highest-impact projects to include in planning roadmaps· provide technical and scientific guidance to your team members· ensure that teams are collecting, understanding, and using data to inform every decision that impacts our customers· stay current with advancements and the latest modeling techniques in the field· publish your research findings in top conferences and journalsAbout You:· Problem Solver: Ability to utilize exceptional problem-solving skills to work through different challenges in ambiguous situations.· Doer: You’ve successfully delivered end-to-end AI/ML projects, working through conflicting viewpoints and data limitations.· Detail Oriented: You have an enviable level of attention to details, and catch things that others miss.· Communicator: Ability to communicate analytical results to senior leaders, peers, and external customers.· Influencer: Innovative scientist with the ability to identify opportunities in a fast-paced and ever-changing environment, and gain support with data and storytelling.Here at Amazon Care, we embrace our differences. We are committed to furthering our culture of inclusion. We have innovative benefit offerings, and we host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.Our team also puts a high value on work-life balance. Striking a healthy balance between your personal and professional life is crucial to your happiness and success here, which is why we aren’t focused on how many hours you spend at work or online. Instead, we’re happy to offer a flexible schedule so you can have a more productive and well- balanced life—both in and outside of work.Amazon is committed to a diverse and inclusive workforce. Amazon is an equal opportunity employer and does not discriminate on the basis of race, ethnicity, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
US, NY, New York
Sponsored Products (SP) is Amazon's largest and fastest growing ad business. SP ads are shown prominently throughout search and product detail pages and allow shoppers to seamlessly discover products sold on Amazon. These are native ads that appear visually similar to other content on the page, which presents a huge opportunity for growth and impact, but also a significant responsibility to protect shopper experience.Job Responsibilities:· Design, develop, and deploy machine learning solutions.· Conduct hands-on data analysis, build large-scale machine-learning models and pipelines.· Work closely with software engineers on detailed requirements, technical designs and implementation of end-to-end solutions in production.· Run regular A/B experiments, gather data, perform statistical analysis, and communicate the impact to senior leaders.· Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.· Provide technical leadership, research new machine learning approaches to drive continued scientific innovation.· Be a member of the Amazon-wide Machine Learning Community, participating in internal and external MeetUps, Hackathons and Conferences.Impact and Career Growth:· Opportunity to grow and broaden your machine learning skills a make impact – the work you deliver directly impacts customers and revenue!· Work in an environment that thrives on creativity, experimentation, and product innovation.· Drive real-time algorithms to allocate billions of ads per day in advertising auctions.· Have the ability to experiment autonomously with meaningful projects.· Mentor others.Why you love this opportunity:Amazon is investing heavily in building a world class advertising business and we are responsible for defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities.
SG, Singapore
The Amazon Prime Team is hiring Interns in Economics. We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to apply economic and econometric theories to large-scale business problems and big data sets.These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. You will work in a team of economists, data scientists, and engineers and in collaboration with product and finance managers. These experiences will translate well into writing applied chapters in your dissertation and prepare you with placement in academia or private sector.Roughly 50% of research assistants from previous cohorts have converted to full time data science or economics employment at Amazon. If you are interested, please send your CV to our mailing list at econ-internship@amazon.com.
US, WA, Seattle
Interested in using AI to improve the shopping experience of millions of customers? Amazon Search has the perfect job for you.Amazon Search Customer Experience is looking for an experienced scientist to lead the innovation in Search Whole Page Optimization (WPO). Your research spans deep learning, reinforcement learning, and personalized recommendations. You will work with a team of scientists and engineers to make Amazon’s search experience intelligent, intuitive, and enjoyable.A successful candidate has strong customer obsession, highly-cited publications in relevant areas, and a track record of deploying research outcomes in production. You will bring deep technical expertise and strong business acumen. Amazon leaders are visionaries who are not afraid of rolling up their sleeves and getting their hands dirty. You will help shape the future of Amazon’s search customer experience by painting a compelling vision and leading the journey to get there. You must have the desire to make industry-wide impact and the ability to work within a fast moving environment to rapidly deliver innovations.As a senior leader, you will be responsible for the holistic optimization of Amazon search pages. From page layout to content ranking, from the navigation experience to product display optimization, you will rethink the assumptions behind traditional e-commerce experience and leverage AI to make the shopping journey of each customer a delightful one. You will be part of the Search technical leadership community that forms the backbone of the company. You will play a critical role in business planning, work closely with senior executives, and influence our long-term technical and business strategy.If you like the challenges and opportunities in this exciting space, come join us to work hard, have fun, and make history.
US, WA, Seattle
The Amazon Shipping is hiring Interns in Economics. We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to apply what they've learned in an academic setting to a business environment, specifically focused on time series forecasting for routing problems.These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. You will learn how to build data sets and perform applied econometric analysis at Internet speed collaborating with economists, data scientists and MBAʼs. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement.Roughly 50% of research assistants from previous cohorts have converted to full time data science or economics employment at Amazon. If you are interested, please send your CV to our mailing list at econ-internship@amazon.com.Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation
US, WA, Seattle
Amazon is looking for a creative Senior Research Scientist to tackle some of the most interesting problems on the leading edge of natural language processing (NLP), machine learning (ML), search and related areas with our Alexa AI team. Alexa AI aims to reinvent search and information retrieval for a voice-forward, multi-modal future. It enables customers to interact with unstructured and semi-structured content via a broad range of technologies including question answering, summarization, search, and multi-turn dialogues.If you are looking for an opportunity to solve deep technical problems and build innovative solutions in a fast-paced environment working within a smart and passionate team, this might be the role for you. You will develop and implement novel scalable algorithms and modeling techniques to advance the state-of-the-art in technology areas at the intersection of ML, NLP, search, and deep learning. You will innovate, help move the needle for research in these exciting areas and build cutting-edge technologies that enable delightful experiences for hundreds of millions of people.In this role you will:· Work collaboratively with other scientists and developers to design and implement scalable models for accessing and presenting information;· · Drive scalable solutions from the business to prototyping, production testing and through engineering directly to production;· · Drive best practices on the team, deal with ambiguity and competing objectives, and mentor and guide junior members to achieve their career growth potential.