We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day. We optimize product placements using a combination of machine learning and natural language processing (NLP) algorithms operating in low latency, high-volume systems. We are highly motivated, collaborative and fun-loving, with entrepreneurial drive and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities.
We are looking for an Applied Scientist to join the Whole-page Advertising Experiences (Waves) team in Marketplace Intelligence with a broad mandate to experiment and innovate to grow Sponsored Products. As an Applied Scientist on this team, you will help to identify unique opportunities to create customized and delightful shopping experience for our growing marketplaces worldwide. Your job will be to identify big opportunities for the team that can help to grow Sponsored Products business working with search and retail partner teams, software engineers and product managers. You will have the opportunity to design, run, and analyze A/B experiments that 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
- 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 both improve the shopper experience while increasing traffic monetization and merchandise sales.
- Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity.
- 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 Scientists to the team and provide mentorship.
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
- Experience building machine learning models or developing algorithms for business application
PREFERRED QUALIFICATIONS
- Experience using Unix/Linux
- Experience in professional software development
- 3+ years of building machine learning models or developing algorithms for business application experience
- 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
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 $222,200/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.