Applied Scientist II

Job ID: 1326829 | Amazon.com Services LLC

DESCRIPTION

We are growing our collaborative group of engineers and applied scientists by expanding into new areas. Come and join us as we invent new ways to delight Amazon customers.

We are Amazon's Global Search Quality team. Our goal is to understand what customers are looking for in whatever language happens to be their choice at the moment and help them find what they need in Amazon's vast catalog of billions of products.

As an. Applied Scientist you will push boundaries in query understanding, semantic matching (e.g. is a drone the same as quadcopter?), relevance ranking (what is a "funny halloween costume"?), language identification (did the customer just switch to their mother tongue?), machine translation (猫の餌を注文する).

Do no hesitate to reach out if you have some of the following: ability to apply state of the art in large scale Machine Learning (e.g. semi-weakly-un-supervised deep learning, natural language understanding), curiosity to learn through controlled experimentation or experience with low latency production systems.


Like everyone else on the team, you will be regularly rewarded by measurable impact on customers like ourselves.

We are an inclusive employer and value diversity at Amazon. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.



Apply now or ping Vaclav Petricek (https://www.linkedin.com/in/petricek) to learn more about the different ways you can have huge impact with us.



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BASIC QUALIFICATIONS

· Master's degree in Computer Science or equivalent
· 3+ years experience in Software development
· 3+ years experience applying Data Science
· Excellent verbal and written communication skills
· Proficiency in one statically typed language (Java, C, C++, …)
· Proficiency in one scripting language (Python, Perl, …)
· Familiarity with a version control system.

PREFERRED QUALIFICATIONS

· Quantitative PhD a plus
· Experience working with real-world noisy data
· Strong problem solving skills
· Knowledge of foreign language(s)