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Home›Jobs›Amazon›Sr. Applied Scientist, NA Store Trends Program
Amazon

About Amazon

The everything store and cloud computing leader

🏢 Tech👥 1001+ employees📅 Founded 1995📍 South Lake Union, Seattle, WA⭐ 3.7
B2CB2BMarketplaceCloud ComputingeCommerce

Key Highlights

  • Headquartered in South Lake Union, Seattle, WA
  • Over 1.5 million employees worldwide
  • Leading cloud services through Amazon Web Services (AWS)
  • Acquired Whole Foods, Twitch, and Ring

Amazon, headquartered in South Lake Union, Seattle, WA, is the world's largest online retailer and a leader in cloud computing through Amazon Web Services (AWS). With over 1.5 million employees globally, Amazon operates in various sectors, including AI with its Alexa devices and a vast marketplace k...

🎁 Benefits

Amazon offers competitive salaries, stock options, generous PTO policies, and comprehensive health benefits. Employees also have access to a learning ...

🌟 Culture

Amazon's culture is driven by customer obsession and a focus on innovation. The company encourages employees to think big and move fast, fostering an ...

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Amazon

Sr. Applied Scientist, NA Store Trends Program

Amazon • Seattle, Washington, USA

Posted 6 months ago🏛️ On-SiteSeniorLeadApplied scientist📍 Seattle
Apply Now →

Job Description

Customers love discovering what is trending, esp. shopping in categories like fashion where customers are looking for inspiration and fashionable styles. Trending products spark curiosity, build confidence, and reassure them they’re making smart choices. Highlighting these trending items and brands on Amazon not only satisfies their desire to stay current but also enhances the overall shopping experience, driving deeper engagement. This newly formed charter in North America Store (NAS) focuses on developing various LLM and ML-driven trend signals (e.g. vital trends, fashionable trending styles, seasonable trends, locale trends, sports or events/holiday trends, niche and trending brands) and solutions leveraging both Amazon internal and external world knowledge to help customers easily discover trending brands and products on Amazon, and enable us to surface these high-interest products in real time and empower any team across Amazon to tap into this intelligence for their specific use cases. In addition, we're in this early stage of exploring exciting opportunities to build AI agents to provide marketing and other clients trend insights to assist clients making the right business decisions.
We're looking for a lead Sr. Applied Scientist who can play the thought leadership role for this ML-focused Trends program as well as collaborating with Product leaders, engineering teams and other scientists to deliver scalable solutions with large business and customer impact.


Key job responsibilities
- Lead complex projects that design and build LLM and ML solutions identifying trending themes and recommendations, as well as AI agents to provide trends insights.
- Collaborate with own and partner teams on customer-facing experiences that will utilize the data and ML models to better serve customers discovery needs on trending products and brands.
- Perform hands-on data analysis, build machine-learning models, run regular A/B tests, and communicate the impact to senior management.
- Drive continued scientific innovation as a thought leader and practitioner.
- Provide technical and career development guidance to scientists and engineers in the organization.


About the team
This newly formed charter in North America Store (NAS) focuses on developing various LLM and ML-driven trend signals (e.g. vital trends, fashionable trending styles, seasonable trends, locale trends, sports or events/holiday trends, niche and trending brands) and solutions leveraging both Amazon internal and external world knowledge to help customers easily discover trending brands and products on Amazon, and enable us to surface these high-interest products in real time and empower any team across Amazon to tap into this intelligence for their specific use cases. In addition, we're in this early stage of exploring exciting opportunities to build AI agents to provide marketing and other clients trend insights to assist clients making the right business decisions. - 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.

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