Senior Applied Scientist, Brand Experience
DESCRIPTION:
The Brand Experience (BX) organization creates, builds and leads innovation for Brand Owners in the Amazon store worldwide. Our growing portfolio of BX tools enable Brands to tell their unique Brand and product stories, optimize content through statistical experimentation, solicit and manage reviews to earn Customer trust and grow their business as well as engage with new and loyal Customers through a variety of channels.
We are looking for a Senior Applied Scientist to lead us to identify data-driven insight and opportunities to improve Brands' success. As a successful applied scientist on our talented team of scientists and engineers, you will solve complex problems to identify actionable opportunities, and collaborate with engineering, research, and business teams for future innovation. You need to be a sophisticated user and builder of statistical models and put them in production to answer specific business questions. You are an expert at synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication. You will continue to contribute to the research community, by working with scientists across Amazon, as well as collaborating with academic researchers and publishing papers (www.aboutamazon.com/research).
Key job responsibilities
As a Sr. Applied Scientist in the team, you will:
- Identify opportunities to improve Brand Experience on Amazon and translate those opportunities into science problems via principled statistical solutions (e.g. ML, causal, RL).
- Mentor and guide the applied scientists in our organization and hold us to a high standard of technical rigor and excellence in MLOps.
- Design and lead roadmaps for complex science projects to help Brands while creating long term value for our shoppers.
- Work with our engineering partners and draw upon your experience to meet latency and other system constraints.
- Identify untapped, high-risk technical and scientific directions, and simulate new research directions that you will drive to completion and deliver.
- Be responsible for communicating our science innovations to the broader internal & external scientific community.
We are open to hiring candidates to work out of one of the following locations:
Seattle, WA, USA
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
- 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.
- Effective verbal and written communication skills with non-technical and technical audiences.
- Experience working with large real-world data sets and building scalable models from big data.
- Exhibits excellent business judgment; balances business, product, and technology very well.
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 $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.
