Description

　　We, Brand Posts & Feeds team builds experiences that connect brands to their shoppers through authentic, lifestyle content and enable brands to communicate their values to shoppers on Amazon. Brands create rich image and video content through Posts, which help shoppers across Amazon’s shopping journey on Search, Detail Page and in Feed experiences. We help create, sustain and deepen the connection between brands and their consumers on Amazon to help make better shopping decisions. We empower brands of all sizes, to tell their story in their own unique voice to consumers. Brands utilize our products to create delightful and engaging shopping experiences that assist shoppers in discovering and evaluating them as part of purchase decisions. We succeed when brands can attract and retain shopper’s attention using our products. Greater brand awareness and engagement with brands result in increased sales for the brand on Amazon. Brands utilize content and data from our products in their advertising campaigns to drive their target shoppers to our products. As the flywheel turns, our success is materialized in terms higher sales at Amazon and increasing Ad spend aimed at driving traffic to our products.

　　We are looking for a Senior Applied Scientist to lead the generation of data driven insights that bring long term value to brands, as well as the ideation and creation of ranking models for brand content. In this role you will influence our team’s science and business strategy with your analyses. You will be expected to identify and solve ambiguous problems and science deficiencies, and to provide informed solutions based on state of the art machine learning research.

　　Why you will love this opportunity: Amazon is investing heavily in building a world-class advertising business. This team collaborate closely with other 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 millions of impressions and 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.

　　Careers at Amazon Advertising https://youtu.be/zD_6Lzw8raE

　　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

　　The Brand Posts & Feeds Science Team develops and deploys into production Machine Learning Algorithms that quantify relevance, select and organize brands’ pieces of content in different placements in Amazon.com. Our goal is to create engaging and enjoyable shopping experiences that incentivize brand discovery and that foster brand customer relationships.

　　We are open to hiring candidates to work out of one of the following locations:

　　Seattle, WA, USA

　　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

　　Knowledge of programming languages such as C/C++, Python, Java or Perl

　　Experience programming in Java, C++, Python or related language

　　Experience with neural deep learning methods and machine learning

　　Preferred Qualifications

　　Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.

　　Experience with large scale distributed systems such as Hadoop, Spark etc.

　　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 $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. Applicants should apply via our internal or external career site.