Amazon Scholars

Amazon is proud to hire world-class academics as Amazon Scholars to work on large-scale technical challenges while continuing to teach and conduct research at their universities.

Scholars_Logo (002)

Amazon is deeply invested in R&D with hundreds of researchers and applied scientists committed to innovation across every part of the company.

The Amazon Scholars program has broadened opportunities for academics to join Amazon in a flexible capacity, in particular part-time arrangements and sabbaticals.

The program is designed for academics from universities around the globe who want to apply research methods in practice and help us solve hard technical challenges without leaving their academic institutions. We believe that Amazon is a unique place to measure the impact of new scientific ideas, given our scale and our ownership of both an information infrastructure and physical infrastructure. You will have a chance to have a ground-up impact on our systems, our business, and most importantly, our customers, through your expertise.

I love developing algorithms and building systems that work in every-day products. Being an Amazon Scholar allows me to do this at a scale far beyond my university role.
Thorsten Joachims Amazon Scholar.jpg
Thorsten Joachims, Professor of Computer Science/ML, Cornell University

Applications are accepted from academic experts in research areas including, but not limited to, the following: Artificial Intelligence, Avionics, Computer Vision, Data Science, Economics, Machine Learning, Optimization, Natural Language Processing, Quantum Computing, and Robotics.

As an Amazon Scholar, your responsibilities may include:

  1. Advising business leaders on strategic plans,
  2. Diving deep to solve a specific technical problem in an organization’s roadmap, and
  3. Advising junior researchers on methods.

We’re working on the future here at Amazon. Come join us!

Program requirements

Basic qualifications:

  • PhD in a relevant field or related discipline
  • 7+ years of relevant work or academic experience
  • Experience leading technical research projects with multiple stakeholders
  • Current affiliation with an academic or research institution

Preferred qualifications:

  • Recognized expert in the external community in an applied science discipline and routinely applies knowledge from other disciplines
  • Publications at top-tier, peer-reviewed conferences and/or journals
  • Broad knowledge of applied mathematics and foundational understanding of algorithms and computational complexity
  • Expert-level research analysis and technical leadership capabilities
  • Expert knowledge in modeling and performance, operationalization, and scalability of scientific techniques and establishing decision strategies
  • Ability to independently lead research development and analysis in a fast-paced environment
  • Proven track record of innovation in creating novel technologies and advancing the state of the art
  • Exceptional verbal and written communication and consensus-building skills with both technical and non-technical audiences

Research locations

Amazon Scholars can work in any Amazon location across the globe where research is being conducted or Amazon has a technical workforce. Scholars can also work remotely, team-permitting.

Amazon has research hubs in the following cities: Aachen, Arlington, Atlanta, Austin, Bay Area, Bangalore, Boston, Barcelona, Beijing, Berlin, Cambridge, Edinburgh, Gdansk, Graz, Haifa, Los Angeles, Luxembourg, New York, Pittsburgh, Seattle, Tel Aviv, Tübingen, Turin, and Vancouver.

How to apply

Accomplished academics who are interested to learn more about how their research may match the challenges, opportunities, and scale of Amazon are encouraged to reach out to scholars-interest@amazon.com for more information.


Work with us

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US, WA, Seattle
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US, WA, Seattle
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US, WA, Seattle
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US, WA, Seattle
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DE, BE, Berlin
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US, WA, Seattle
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IN, MH, Mumbai
Amazon Science gives you insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work.Please visit https://www.amazon.science for more information.About Amazon Prime Video“Many of the problems we face have no textbook solution, and so we-happily-invent new ones.” – Jeff Bezos
The Amazon Prime Video team is shaping the future of digital video entertainment. We are seeking an outstanding Data Scientist to uncover key insights on how consumers watch videos on Amazon. The ideal candidate will be an expert in the areas of data science, machine learning and statistics, having hands-on experience with multiple improvement initiatives as well as balancing technical and business judgment to make the right decisions about technology, models and methodologies.As consumers increasingly consume digital video, we need to make agile decisions based on what content appeals to our customers. As a Data Scientist at Amazon Prime Video, you will have the opportunity to work on one of the world's largest consumer data sets, influence the long term evolution of our analytics capability and support the expansion of Amazon's digital video business. The Data Scientist will work closely with other research scientists, machine-learning experts, and economists to design and run experiments, research new algorithms, and find new ways to improve optimization across all our associate facing tools. 
A successful candidate will be able to understand and manage key operational and technical concepts. They will have excellent project and communication skills, and motivation to achieve results in a fast-paced environment. Candidates should demonstrate a passion for working on behalf of customers, have a record of accomplishment of timely delivery of large-scale projects, and have the ability to influence multiple global teams. Autonomy, judgment, influence, and leadership skills are essential. This person will be responsible for ensuring we meet our key deliverables, on time with high quality, and communicating status to internal and external stakeholders.Key Responsibilities- Support the Content team on business reporting, ad hoc analysis, statistical inference and predictive modelling for all Prime Video India.- Mine and analyze data pertaining to customers viewing experiences to identify critical business insight and make recommendations to optimize content selection.- Proactively develop new ML models using streaming, video, audio and textual data to understand and predict customer streaming behaviour- Translate analytic insights into concrete, actionable recommendations for business or product improvement. Develop and present these as papers to senior stakeholders.- Liaise with your peers in other prime video territories to develop solutions that greatly benefit our global customers- This role will be based in Mumbai, India
JP, 13, Meguro
We are seeking an experienced Data Scientist Leader to drive the future growth of Amazon Prime in Japan. Our vision is for Prime to be the Earth’s largest and most loved membership program. Within Japan, we aim to be a center of innovation for Prime and Amazon, and to delight our members with the value and convenience of Prime benefits.The Data Scientist, JP Prime will manage customer behavior data and lead our customer-obsessed/data-driven decision making for the Amazon Prime Program in Japan. This leader will work with Product/Marketing, Economist, Finance, and Data Engineering teams across the globe as a pivotal leader, diving deep into data to identify actionable customer insights that will improve the value of the Prime program in Japan, as well as empower our product/marketing strategy to grow and engage Prime members. Success in this role includes solving complex business issues through analytical solutions, influencing the team’s product/marketing strategy at a large scale, and contributing significantly to business planning.Primary Responsibilities:- Creating a roadmap of challenging business questions on how we grow membership, engage members, and improve value of Amazon Prime, using data to articulate possible root cause analysis and solutions.- Managing and executing entire projects or components of large projects from start to finish including project management, data gathering and manipulation, synthesis and modeling, problem solving, and communication of insights and recommendations.- Working closely with other research scientists, machine learning experts, and economists to design and run experiments, research new algorithms, and find new ways to improve analytics, prove incrementality and drive growth.- Partnering with technology and product leaders to solve business and technology problems using scientific approaches to build new services that surprise and delight our customers.- Utilizing Amazon systems and tools to effectively work with terabytes of data.
AU
Are you excited about understanding the state-of-the-art Machine Learning, Natural Language Processing, Deep Learning and Computer Vision algorithms and designs using large data sets to solve real world problems?A research internship at Amazon Adelaide is an opportunity to work with leading machine learning researchers on incomparable datasets using the best tools and hardware in the world. It is an opportunity for PhD students and recent graduates in Computer Vision, Deep Learning, Natural Language Processing, and broader Machine Learning to address challenges at a scale that is impossible elsewhere. Along the way, you’ll get opportunities to be a disruptor, prolific innovator, and a reputed problem solver—someone who truly enables machine learning to create significant impact.As an Applied Scientist Intern, you will be working in a fast-paced, cross-disciplinary team of researchers who are pioneers in the field. You will take on complex problems, and work on solutions that either leverage existing academic and industrial research, or utilize your own out-of-the-box pragmatic thinking. In addition to coming up with novel solutions and prototypes, you may even need to deliver these to production in customer facing products