Seattle, WA, 98194, USA
2 days ago
Senior Applied Scientist, Sponsored Products and Brands
Description **About Sponsored Products and Brands** The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. **About our team** The Amazon Brand Store team (such as www.amazon.com/lego) within Sponsored Products and Brands is a core product offering in the Amazon Advertising portfolio. The brand’s store are their dedicated place on Amazon to differentiate, grow sales, and build loyalty with millions of shoppers. Our mission is to empower brands of all sizes to tell their story in their own unique voice to consumers. We help brands create engaging shopping experiences that assist shoppers in discovering and evaluating them as part of their purchase decisions. We succeed when we are both useful to shoppers and when brands can attract and retain shopper’s attention using our products. A cool case study on brand stores can be found here: https://advertising.amazon.com/library/case-studies/nespresso-brand-store-increases-shopper-engagement. 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 personalized shopping experiences for brand stores through industry-leading generative AI technologies. In this role, you will influence our team's science and business strategy with your expertise and deep business understanding. 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. **Impact and Career Growth** You will invent new experiences and influence customer-facing shopping experiences to help brands grow their retail businesses. This is your opportunity to work within the fastest-growing businesses across all of Amazon! You'll define a long-term science vision for AI-driven brand shopping experiences, working backwards from our customers' needs and 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. 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. 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 large scale machine learning systems such as profiling and debugging and understanding of system performance and scalability - Experience with large scale distributed systems such as Hadoop, Spark etc. 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. 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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