As a Senior Applied Scientist on our team, you will be responsible for defining the science and technical strategy for one of our most impactful marketplace controls, creating lasting value for Amazon and our advertising customers. You will help to identify unique opportunities to create customized and delightful shopping experience for our growing marketplaces worldwide. Your job will be identify big opportunities for the team that can help to grow Sponsored Products business working with retail partner teams, Product managers, Software engineers and PMs. You will have opportunity to design, run and analyze A/B experiments to improve the experience of millions of Amazon shoppers while driving quantifiable revenue impact. More importantly, you will have the opportunity to broaden your technical skills in an environment that thrives on creativity, experimentation, and product innovation.
Key job responsibilities
- Lead science, tech and business strategy and roadmap for Sponsored Products Monetization
- Drive alignment across multiple organizations for science, engineering and product strategy to achieve business goals
- Lead and mentor scientists and engineers across teams to develop, test, launch and improve of science models designed to optimize the shopper experience and deliver long term value for Amazon and advertisers
- Develop state of the art experimental approaches and ML models
- Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity
- 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 Scientists to the team and provide mentorship
BASIC QUALIFICATIONS
- 5+ years of building machine learning models for business application experience
- PhD, or Master's degree and 5+ years of applied research experience
- 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 $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.