Senior Applied Scientist, Ads Marketing Decision Science
Amazon New York
We are seeking a motivated and experienced Senior Applied Scientist with expertise in Machine Learning (ML), Artificial Intelligence (AI), Big Data, and Service Oriented Architecture. You should have a deep understanding of the digital advertising business and scaled marketing across communication channels.
In this role, you will collaborate with a cross-functional team of talented scientists and engineers to innovate, iterate, and solve real-world marketing problems with cutting-edge AWS technologies. You will lead in-depth analyses of the key problems faced by Amazon Ads customers and the challenges faced by marketing teams in meeting customer needs at scale.
We analyze the needs, experiences, and behaviors of Amazon advertisers at petabytes scale, to deliver the right marketing communications to the right advertiser at the right time. Our products enable applications and synergies across Ads organization, spanning marketing, product, and sales use cases.- 3+ years of building machine learning models for business application 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.
In this role, you will collaborate with a cross-functional team of talented scientists and engineers to innovate, iterate, and solve real-world marketing problems with cutting-edge AWS technologies. You will lead in-depth analyses of the key problems faced by Amazon Ads customers and the challenges faced by marketing teams in meeting customer needs at scale.
To address these problems, you will build innovative large-scale ML/AI solutions such as bespoke omni-channel recommender systems, and specialized LLM-powered assistants for customers and marketers. You will independently drive research and prototyping to deliver functional proofs of concept (POCs), and then partner with engineers to inform the technology roadmap and deploy successful POCs as scalable batch and real-time applications in production.
Key job responsibilities- Define and execute a research and development plan that enables data-driven marketing decisions and delivers inspiring customer experiences
- Evaluate, evolve, and invent scientific techniques to effectively address customer needs and business problems
- Establish and drive science prototyping best practices to ensure coherence and integrity of data feeding into production ML/AI solutions
- Collaborate with colleagues across science and engineering disciplines for rapid prototyping at scale
- Partner with engineering teams to solve complex technical problems, define system-level requirements, develop implementation plans, and guide the adaptation of techniques to meet production needs
- Partner with product managers and stakeholders to define forward-looking product visions and prospective business use-cases
- Drive and lead of culture of data-driven innovation within and outside across Amazon Ads Marketing organization
- Influence organizational vision across Ads Marketing organization
About the team
The Marketing Decisions Science team provides AI/ML products to enable Amazon Ads Marketing to deliver relevant and compelling guidance, education, and inspiration to prospective and active advertisers across marketing channels. We own the product, technology, and deployment roadmap for AI/ML products across Amazon Ads Marketing.We analyze the needs, experiences, and behaviors of Amazon advertisers at petabytes scale, to deliver the right marketing communications to the right advertiser at the right time. Our products enable applications and synergies across Ads organization, spanning marketing, product, and sales use cases.- 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 Generative AI (Gen-AI) methods, such as supervised funetuning, reinforcement learning from human feedback (RLHF), direct preference optimization (DPO)- 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.
- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
- Experience with designing, deploying and operating large scale recommender systems in production
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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