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Applied Scientist, Detail Page Allocation & Pricing

Amazon

Seattle (WA)

On-site

USD 136,000 - 224,000

Full time

30+ days ago

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Job summary

An established industry player is seeking an Applied Scientist to join their innovative advertising team. In this pivotal role, you will develop cutting-edge machine learning models that optimize ad placements and enhance user experience. Collaborating with a talented team of scientists and engineers, you'll tackle complex challenges and drive impactful projects that directly influence revenue and customer satisfaction. This is a unique opportunity to be part of a rapidly growing sector, where your contributions will shape the future of advertising technology. If you're passionate about data-driven strategies and eager to make a significant impact, this role is perfect for you.

Benefits

Medical Benefits
Financial Benefits
Equity Options
Flexible Work Environment

Qualifications

  • 3+ years of experience building models for business applications.
  • PhD or Master's with 4+ years in CS, CE, ML or related fields.

Responsibilities

  • Build machine learning models to solve business problems.
  • Run A/B experiments and perform statistical analysis.
  • Collaborate with software engineers for end-to-end solutions.

Skills

Machine Learning
Data Analysis
Statistical Analysis
Programming (Java, C++, Python)
Algorithms and Data Structures
Numerical Optimization

Education

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

Tools

Unix/Linux

Job description

Job ID: 2944162 | Amazon.com Services LLC

Amazon is building a world class advertising business and defining and delivering a collection of self-service performance advertising products that drive discovery and sales of merchandise. Our products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities.

As an Applied Scientist for the Sponsored Products Detail Page Allocation and Pricing team, you develop systems which make the final decision on which ads to show, where to place them on the page and how many ads to place. This also includes selection of various themes that would appear in detail pages. This is a challenging technical and business problem, which requires us to balance the interests of advertisers, shoppers, and Amazon. You'll develop a data-driven product strategy to define the right quantitative measures of shopper impact, using this to evaluate decisions and opportunities. You'll balance a portfolio of pragmatic and long-term investments to drive long term growth of the ads and retail businesses. You'll develop real-time algorithms to allocate billions of ads per day in advertising auctions.

Impact and Career Growth:

In this role you will have significant impact on this team as well as drive cross team projects that consist of Applied Scientists, Data Scientists, Economists, and Software Development Engineers. This is a highly visible role that will help take our products to the next level. You will work alongside many of the best and brightest science and engineering talent and the work you deliver will have a direct impact on customers and revenue!

Key job responsibilities
  1. Build machine learning models and utilize data analysis to deliver scalable solutions to business problems.
  2. Run A/B experiments, gather data, and perform statistical analysis.
  3. Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.
  4. Work closely with software engineers on detailed requirements, technical designs and implementation of end-to-end solutions in production.
  5. Research new machine learning approaches.
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 committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, 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 this link 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 this link.

This position will remain posted until filled. Applicants should apply via our internal or external career site.

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