Publication

Beyond accurate answers: Evaluating open-domain question answering in enterprise search

By Daniel Zhou, Lan Liu, Anmol Anubhai, Maansi Shandilya, Steph Sigalas, William Wang, Zhiheng Huang

2023

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Open-domain question answering (OpenQA) research has grown rapidly in recent years. However, OpenQA usability evaluation in its real world applications is largely left under studied. In this paper, we evaluated the actual user experience of OpenQA model deployed in a large tech company’s production enterprise search portal. From qualitative query log analysis and user interviews, our preliminary findings are: 1) There exists a large number of “contingency answers” that cannot be simply evaluated against their face textual values, due to noisy source passages and ambiguous query intents from short keywords queries. 2) Contingency answers contribute to positive search experience for providing “information scents”. 3) Click-through-rate (CTR) is a good user-behavior metric to measure OpenQA result quality, despite the rare existence of “good abandonment”. This exploratory study reveals an often neglected gap between existing OpenQA research and its search engine applications that disconnects the offline research effort with online user experience. We call for reformulating OpenQA model objective beyond answer face value and developing new dataset and metrics for better evaluation protocols.

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Staff writer

September 20, 2023

Leveraging large language models will make interactions with Alexa more natural and engaging.

Conversational AI / Natural-language processing
The science behind the new FBA capacity management system

Staff writer

September 19, 2023

The new Fulfillment by Amazon system empowers sellers to have more transparency and control over their capacity within Amazon’s fullfilment network by applying market-based principles.

Operations research and optimization
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Zhihan Gao, Boran Han

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Novel “cuboid attention” helps transformers handle large-scale multidimensional data, while diffusion models enable probabilistic prediction.

Machine learning

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US, CA, Sunnyvale

At Amazon Fashion, we are obsessed with making Amazon Fashion the most loved fashion destinations globally. We're searching for Computer Vision pioneers who are passionate about technology, innovation, and customer experience, and who are enthusiastic about making a lasting impact on the industry. You'll be working with talented scientists, engineers, and product managers to innovate on behalf of our customers. If you're fired up about being part of a dynamic, driven team, then this is your moment to join us on this exciting journey and change the world of eCommerce forever Key job responsibilities As a Applied Scientist, you will be at the forefront to define, own and drive the science that span multiple machine learning models and enabling multiple product/engineering teams and organizations. You will partner with product management and technical leadership to identify opportunities to innovate customer facing experiences. You will identify new areas of investment and work to align product roadmaps to deliver on these opportunities. As a science leader, you will not only develop unique scientific solutions, but more importantly influence strategy and outcomes across different Amazon organizations such as Search, Personalization and more. This role is inherently cross-functional and requires a strong ability to communicate, influence and earn the trust of software engineers, technical and business leadership. We are open to hiring candidates to work out of one of the following locations: Sunnyvale, CA, USA

Applied Scientist

GB, Cambridge

Our team undertakes research together with multiple organizations to advance the state-of-the-art in speech technologies. We not only work on giving Alexa, the ground-breaking service that powers Echo, her voice, but we also develop cutting-edge technologies with Amazon Studios, the provider of original content for Prime Video. Do you want to be part of the team developing the latest technology that impacts the customer experience of ground-breaking products? Then come join us and make history. We are looking for a passionate, talented, and inventive Senior Applied Scientist with a background in Machine Learning to help build industry-leading Speech, Language and Video technology. As a Senior Applied Scientist at Amazon you will work with talented peers to develop novel algorithms and modelling techniques to drive the state of the art in speech and vocal arts synthesis. Position Responsibilities: - Participate in the design, development, evaluation, deployment and updating of data-driven models for digital vocal arts applications. - Participate in research activities including the application and evaluation and digital vocal and video arts techniques for novel applications. - Research and implement novel ML and statistical approaches to add value to the business. - Mentor junior engineers and scientists. We are open to hiring candidates to work out of one of the following locations: Cambridge, GBR

Intern - Economics, PXT Central Science

US, WA, Seattle

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Senior Applied Scientist, Sponsored Products

US, NY, New York

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Senior Applied Scientist, Amazon

US, VA, Arlington

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US, WA, Seattle

Amazon Advertising Impact Team is looking for a Senior Economist to help translate cutting-edge causal inference and machine learning research into production solutions. The individual will have the opportunity to shape the technical and strategic vision of a highly ambiguous problem space, and deliver measurable business impacts via cross-team and cross-functional collaboration. Amazon is investing heavily in building a world class advertising business. Our advertising products are strategically important to Amazon’s Retail and Marketplace businesses for driving long-term growth. The mission of the Advertising Impact Team is to make our advertising products the most customer-centric in the world. We specialize in measuring and modeling the short- and long-term customer behavior in relation to advertising, using state of the art econometrics and machine learning techniques. With a broad mandate to experiment and innovate, we are constantly advancing our experimentation methodology and infrastructure to accelerate learning and scale impacts. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. Key job responsibilities • Function as a technical leader to shape the strategic vision and the science roadmap of a highly ambiguous problem space • Develop economic theory and deliver econometrics and machine learning models to optimize advertising strategies on behalf of our customers • Design, execute, and analyze experiments to verify the efficacy of different scientific solutions in production • Partner with cross-team technical contributors (scientists, software engineers, product managers) to implement the solution in production • Write effective business narratives and scientific papers to communicate to both business and technical audience, including the most senior leaders of the company We are open to hiring candidates to work out of one of the following locations: New York, NY, USA | Seattle, WA, USA

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US, WA, Seattle

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US, VA, Arlington

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Actuarial Analyst, Global Risk Management & Claims

US, WA, Seattle

We are expanding our Global Risk Management & Claims team and insurance program support for Amazon’s growing risk portfolio. This role will partner with our risk managers to develop pricing models, determine rate adequacy, build underwriting and claims dashboards, estimate reserves, and provide other analytical support for financially prudent decision making. As a member of the Global Risk Management team, this role will provide actuarial support for Amazon’s worldwide operation. Key job responsibilities ● Collaborate with risk management and claims team to identify insurance gaps, propose solutions, and measure impacts insurance brings to the business ● Develop pricing mechanisms for new and existing insurance programs utilizing actuarial skills and training in innovative ways ● Build actuarial forecasts and analyses for businesses under rapid growth, including trend studies, loss distribution analysis, ILF development, and industry benchmarks ● Design actual vs expected and other metrics dashboards to assist decision makings in pricing analysis ● Create processes to monitor loss cost and trends ● Propose and implement loss prevention initiatives with impact on insurance pricing in mind ● Advise underwriting decisions with analysis on driver risk profile ● Support insurance cost budgeting activities ● Collaborate with external vendors and other internal analytics teams to extract insurance insight ● Conduct other ad hoc pricing analyses and risk modeling as needed We are open to hiring candidates to work out of one of the following locations: Arlington, VA, USA | New York, NY, USA | Seattle, WA, USA

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US, WA, Seattle

The economics team within Recruiting Engine uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, well-being, and the value of work to Amazonians. We are an interdisciplinary team, which uses a range of approaches to develop and deliver solutions that measurably achieve this goal. We are looking for an Economist who is able to provide structure around complex business problems, hone those complex problems into specific, scientific questions, and test those questions to generate insights. The ideal candidate will work with various science, engineering, operations and analytics teams to estimate models and algorithms on large scale data, design pilots and measure their impact, and transform successful prototypes into improved policies and programs at scale. She/He/They will produce robust, objective research results and insights which can be communicated to a broad audience inside and outside of Amazon. Ideal candidates will work closely with business partners to develop science that solves the most important business challenges. She/He/They will work well in a team setting with individuals from diverse disciplines and backgrounds. She/He/They will serve as an ambassador for science and a scientific resource for business teams. Ideal candidates will own the development of scientific models and manage the data analysis, modeling, and experimentation that is necessary for estimating and validating the model. They will be customer-centric – clearly communicating scientific approaches and findings to business leaders, listening to and incorporate their feedback, and delivering successful scientific solutions. We are open to hiring candidates to work out of one of the following locations: Arlington, VA, USA | Seattle, WA, USA