Data Scientist, SPX AI Lab

Lensa; Seattle (WA); On-site; USD 100,000 - 216,000; Full time

Job summary

Join a leading tech company as a Data Scientist, contributing to exciting AI initiatives aimed at enhancing the Seller experience on Amazon. You'll work with cutting-edge technologies in a collaborative environment, driving impactful solutions to help businesses thrive. Your expertise in machine learning and data analysis will be vital in designing intuitive experiences for users.

Qualifications

• 2+ years of data scientist experience.
• 3+ years of experience with SQL and scripting languages like Python.
• Experience with machine learning tools and techniques.

Responsibilities

• Use state-of-the-art Machine Learning and Generative AI techniques to create tools for Selling Partners.
• Design, develop, and deploy innovative data models.
• Implement scalable data analysis processes.

Skills

Data analysis

Machine Learning

Scripting languages

Education

Bachelor's or Master's degree in Computer Science or related field

Tools

Python

SQL

Job description

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Description

The Selling Partner Experience (SPX) organization strives to make Amazon the best place for Selling Partners to do business. The SPX AI Lab team is building the AI capabilities powering the Selling Assistant, Amazon's conversational assistant experience for Selling Partners. The Selling Assistant is a trusted partner and a seasoned advisor that’s always available to enable our partners to thrive in Amazon’s stores. It takes away the cognitive load of selling on Amazon by providing a single interface to handle a diverse set of selling needs. The assistant always stays by the seller's side, talks to them in their language, enables them to capitalize on opportunities, and helps them accomplish their business goals with ease. It is powered by the latest advances in Generative AI, going beyond a typical chatbot to provide an intuitive, intelligent, and personalized experience to sellers running real businesses, large and small.

Do you want to join an innovative group of scientists, engineers, and product managers who use state-of-the-art Generative AI and Machine Learning technologies to help Amazon create a delightful Selling Partner experience? Do you want to build solutions to real business problems by automatically understanding and addressing sellers’ challenges, needs and opportunities? Are you excited by the prospect of contributing to one of Amazon’s most strategic Generative AI initiatives? If yes, then you may be a great fit to join the SPX AI Lab team.

Key job responsibilities

• Use state-of-the-art Machine Learning and Generative AI techniques to create the next generation of the tools that empower Amazon's Selling Partners to succeed.
• Design, develop and deploy highly innovative data models to interact with Sellers and delight them with solutions.
• Work closely with teams of scientists, product managers and engineers to drive real-time model implementations and deliver novel and highly impactful features.
• Establish scalable, efficient, automated processes for large scale data analyses, model benchmarking, model validation and model implementation.
• Implement novel machine learning and statistical approaches.
• Participate in strategic initiatives to employ the most recent advances in ML in a fast-paced, experimental environment.
  
  

About The Team

SPX AI Lab is a growing team of scientists driving the research and development of the next generation of GenAI experiences that empower Amazon's Selling Partners to succeed. We draw from many science domains, from Natural Language Processing to Computer Vision to Optimization to Economics, to create solutions that seamlessly and automatically engage with Sellers, solve their problems, and help them grow. We strive to radically simplify the seller experience, lowering the cognitive burden of selling on Amazon by making it easy to accomplish critical tasks such as launching new products, understanding and complying with Amazon’s policies and taking actions to grow their business.

Basic Qualifications

• 2+ years of data scientist experience
• 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
• 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
• Experience applying theoretical models in an applied environment
  
  

Preferred Qualifications

• Experience in Python, Perl, or another scripting language
• Experience in a ML or data scientist role with a large technology company
  
  

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 $125,500/year in our lowest geographic market up to $212,800/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.

If you have questions about this posting, please contact [e-mail]

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Engineering and Information Technology

• Industries

  IT Services and IT Consulting

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