Applied Scientist, Customer - Advertiser Success & Insights, Amazon Advertising

apartmentAmazon placeNew York calendar_month 
Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. 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 Customer - Advertiser Success & Insights (CASI) team is seeking an Applied Scientist to help increase the effectiveness of online advertising. You will leverage computer vision, generative AI, natural language processing, casual inference, and machine learning to enhance the customer experience with online advertising.

In this role, you will collaborate closely with business leaders, stakeholders, and cross-functional teams to drive success for our customers through data-driven solutions.

This is an excellent opportunity for a technically-minded individual to make a tangible impact on the online advertising landscape. The role offers the chance to work with state-of-the-art technologies and contribute to the evolution of a rapidly changing industry.

Key job responsibilities

As an Applied Scientist in CASI, you will: -> Shape the science roadmap for CASI, fostering a culture of data-driven decision-making.

-> Deliver significant business impact through advanced ML models, generative AI, and cutting-edge causal inference methodologies.
-> Produce and deliver models that help drive best-in-class customer experiences and build systems that allow us to deploy these models to production with low latency and high throughput.
-> Collaborate with cross-functional teams, including software engineers, data scientists, and product managers, to define project requirements, establish success metrics, and deliver high-quality solutions.

> Research new and innovative machine learning approaches.

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 in patents or publications at top-tier peer-reviewed conferences or journals
  • 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- Experience using Unix/Linux
  • Experience in professional software development
  • Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers
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.

For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

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 $222,200/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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