Job Information
Amazon Senior Applied Scientist, Sponsored Products in New York, New York
Description
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. 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 Search Relevance team parses billions of ads to surface the best ad to show to Amazon shoppers. The team strives to understand customer intent and identify relevant ads that enable them to discover new and alternate products. This also enables sellers on Amazon to showcase their products to customers, which may, at times, be buried deeper in the search results. By showing the right ads to customers at the right time, this team improves the shopper experience, increase advertiser ROI, and improves long-term monetization. This is a talented team of machine learning scientists and software engineers working on complex solutions to understand the customer intent and present them with ads that are not only relevant to their actual shopping experience but also non-obtrusive. This area is of strategic importance to Amazon Retail and Marketplace business, driving long term growth.
Key job responsibilities
As a Senior Applied Scientist on this team, you will:
Be the technical leader in Machine Learning; lead efforts within this team and across other teams.
Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience.
Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity.
Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models.
Run A/B experiments, gather data, and perform statistical analysis.
Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.
Research new and innovative machine learning approaches.
Recruit Applied Scientists to the team and provide mentorship.
About the team
Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate.
You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding.
Basic Qualifications
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 popular deep learning frameworks such as MxNet and Tensor Flow.
Preferred Qualifications
Experience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalability
Advanced degree in Computer Science, Mathematics, Statistics, Economics, or related quantitative field.
Published research work in academic conferences or industry circles.
Experience in building large-scale machine-learning models and infra for online recommendation, ads ranking, personalization, or search, etc.
Technical leadership in machine learning.
Effective verbal and written communication skills with non-technical and technical audiences.
Experience working with real-world data sets and building scalable models from big data.
Thinks strategically, but stays on top of tactical execution.
Exhibits excellent business judgment; balances business, product, and technology very well.
Experience in computational advertising.
Experience in Large Language Models (LLMs).
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 $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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