Amazon is investing heavily in building a world class advertising business and we are responsible for defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit 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 Monetization team in Marketplace Intelligence with a broad mandate to experiment and innovate to grow Sponsored Products. As an Applied Scientist in 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 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

- 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.

- 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.

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

New York, NY, USA | Santa Monica, CA, USA

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

PREFERRED QUALIFICATIONS

- Experience in professional software development

- PhD in econometrics, statistics, industrial engineering, operations research, optimization, data mining, analytics, or equivalent quantitative field

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.

---