Applied Scientist , Sponsored Products

Amazon; New York (NY); On-site; USD 136,000 - 224,000; Full time

Job summary

Amazon is seeking an experienced Applied Scientist for their Sponsored Products team, which focuses on enhancing product discovery through innovative machine learning techniques. The role involves conducting data analysis, designing experiments, and collaborating with engineering teams to optimize the advertising platform. Candidates should possess strong backgrounds in machine learning and programming, with a PhD or equivalent experience preferred.

Qualifications

• 3+ years of experience building models for business applications.
• Experience in algorithms and data structures.
• Proficient in using statistical techniques for complex problems.

Responsibilities

• Conduct hands-on data analysis and run regular A/B experiments.
• Design, prototype, and test hypotheses in ambiguous environments.
• Establish processes for data analysis and model validation.

Skills

Data analysis

Statistical analysis

Machine learning

Natural language processing

Education

PhD in Computer Science or related field

Master's degree with 4+ years of experience

Tools

Java

C++

Python

Job description

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Description

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. As a core product offering within our advertising portfolio, Sponsored Products (SP) helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The SP team's primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day!

Description

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. As a core product offering within our advertising portfolio, Sponsored Products (SP) helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The SP team's primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day!

The Detail Page Discovery Experiences team is chartered with inventing and building engaging product recommendation experiences in Amazon Product Detail Pages. We push the innovation frontiers for our hundreds of millions of customers WW to aid product discovery while helping shoppers to find relevant products easily. Our team is building differentiated recommendations and utilizing cutting-edge machine learning techniques in the domain of natural language processing (NLP) and Transformer, deep learning, reinforcement learning, and Generative AI to provide delightful shopping experiences and deliver significant impact for the business.

We are looking for an Applied Scientist who can delight our customers by continually learning and inventing. Our ideal candidate is an experienced Applied Scientist who has a track-record of performing deep analysis and is passionate about applying advanced ML and statistical techniques to solve real-world, ambiguous and complex challenges to optimize and improve the product performance, and who is motivated to achieve results in a fast-paced environment. The position offers an exceptional opportunity to grow your technical and non-technical skills and make a real difference to the Amazon Advertising business.

As an Applied Scientist in the Blended Widgets team, you will:

• Conduct hands-on data analysis, and run regular A/B experiments, gather data, perform statistical analysis and deep dive, and communicate the impact to senior management
• Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative analysis and business judgment
• Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving
• Collaborate with software engineering teams to integrate successful experimental results into large-scale, highly complex Amazon production systems
• Promote the culture of experimentation and applied science at Amazon
  
  

Team video https://youtu.be/zD_6Lzw8raE

We are also open to consider the candidate in New York, or Seattle.

Basic Qualifications

• 3+ years of building models for business application experience
• PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
• Experience programming in Java, C++, Python or related language
• Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
  
  

Preferred Qualifications

• Experience using Unix/Linux
• Experience in professional software development
  
  

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

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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 $136,000/year in our lowest geographic market up to $223,400/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.


Company - Amazon.com Services LLC

Job ID: A3001241

Seniority level

• Seniority level

  Not Applicable

Employment type

• Employment type

  Full-time

Job function

• Job function

  Research, Science, and Engineering

• Industries

  Software Development

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