Job summary
Want to work in a start-up environment with the resources of Amazon behind you? Do you want to have direct and immediate impact on millions of customers every day? If you are a self-starter, passionate about machine learning, big data systems, enjoy designing and implementing new features and machine learned models, and intrigued by ambiguous problems, look no further.
Amazon is investing heavily in building world class advertising solutions that shift away from using traditional cookies/identifiers to new modeled machine learning solutions to achieve campaign performance. Our products are strategically important to the advertising business as the intersection of consumer privacy and new ways of advertising is at a critical period of change. We deliver billions of ad impressions and clicks daily and are breaking fresh ground to build new avenues for advertisers.
The Frequency Management team is looking for Applied Scientists to join our hybrid science and engineering team. We are a new team, based in Palo Alto and New York. Our charter is to provide advertisers and agencies a holistic, user privacy centric, frequency management program to maximize in-target audience reach with an optimal frequency across Amazon O&O properties, Audio, Video, Kindle devices and third-party sites.
You’ll be one of the scientists tackling some of the hardest problems in advertising; recommending optimal frequency level for advertisers to maximize reach for their targeted audience. This is a highly visible program across multiple organizations where you will have the opportunity to have a huge impact.
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.
Why you will love this opportunity: 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.
Impact and Career Growth: 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.
Team video https://youtu.be/zD_6Lzw8raE
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.
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.