Applied Scientist, Amazon Search

We are seeking a talented applied researcher to join the Whole Page Planning and Optimization (WPPO) Science team in Search.

The latest data from Business Insider shows that almost 50% of online shoppers visit Amazon first. The Search WPPO Science team is responsible for developing reinforcement learning systems for the next generation Amazon shopping experience and delivering it to millions of customers.

We believe that shopping on Amazon should be simple, delightful, and full of WOW moments for EVERYONE, whether you are technically savvy or new to online shopping.

As an Applied Scientist, you will be working closely with a team of applied scientists and engineers to build systems that shape the future of Amazon's shopping experience by automatically generating relevant content and building a whole page experience that is coherent, dynamic, and interesting.

You will improve ranking and optimization in our algorithm. You will participate in driving features from idea to deployment, and your work will directly impact millions of customers.

You are going to love this job because you will :

• Apply state-of-the-art Machine Learning (ML) algorithms, including Deep Learning and Reinforcement Learning, to improve hundreds of millions of customers’ shopping experience.
• Have measurable business impact using A / B testing.
• Work in a dynamic team that provides continuous opportunities for learning and growth.
• Work with leaders in the field of machine learning.

Joining this team, you’ll experience the benefits of working in a dynamic, entrepreneurial environment, while leveraging the resources of Amazon.

com (AMZN), one of the world's leading internet companies. We provide a highly customer-centric, team-oriented environment.

A successful candidate will have a solid research background in machine learning and reinforcement learning algorithms, customer obsession, great communication skills, and the motivation to achieve results in a fast-paced environment.

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

Palo Alto, CA, USA Seattle, WA, USA

BASIC QUALIFICATIONS

• 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

• Ph.D. in Computer Science, Statistics, Applied Math, or a related quantitative field
• At least 2 years of experience with predictive modeling and analysis, applying various machine learning techniques including supervised / unsupervised learning, deep learning, and reinforcement learning
• At least 1 year of experience building large scale production software system
• Strong publication record at top ML conferences and journals
• Strong verbal and written communications skills; experience presenting complex technical information, succinctly, to technical and non-technical audiences
30+ days ago