Applied Scientist - Advertiser Growth Engine

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. Our products are strategically important to our businesses driving long term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day!

Advertiser Growth Engine (AGE) team owns and builds services and applications across Amazon World-Wide Advertising that make advertising across multi-marketplaces as easy as flipping on a switch. We are focused on: (1) expanding Amazon Ads advertiser base, and (2) eliminating localization, operational, and marketplace knowledge gap barrier for Advertisers who advertise across multiple marketplaces. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth globally.

We're looking for an experienced Applied Scientist with exceptional technical, analytical, and innovative capabilities to research, design, and create elegant machine learning solutions. The solutions will help our advertisers with multi-media and multi-lingual advertising offerings. You will use ideas from various domains of machine learning, including supervised and unsupervised methods, Deep Neural Networks, Natural Language Processing (NLP), and Computer Vision (CV) to build ML models that localizes multi-media advertising contents, including text, images and videos. You will also identify opportunities to leverage ML beyond localization, including, international expansion and global campaigns. Your work will directly impact our customers in the form of products and services used directly by our advertisers as well as our third-party integrators.

As an Applied Scientist on this team, you will:
- Build and deliver end-to-end machine learning solutions; build ML models and perform data analysis to deliver scalable solutions to business problems.
- Perform hands-on analysis and modeling with enormous data sets to develop insights that increase traffic monetization and merchandise sales without compromising shopper experience.
- Work closely with software engineers on detailed requirements to productionize the ML models you build.
- Run A/B experiments that affect hundreds of millions of customers, evaluate the impact of your optimizations and communicate your results to various business stakeholders.
- Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.
- Research new innovate machine learning approaches.

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

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 building machine learning models or developing algorithms for business application
- Experience developing and implementing deep learning algorithms, particularly with respect to computer vision algorithms
- Experience with popular deep learning frameworks such as MxNet and Tensor Flow
- Experience in designing experiments and statistical analysis of results
- 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.

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.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.