Data Scientist, Automatic Speech Recognition

DESCRIPTION

Amazon is looking for a passionate, talented, and inventive Data Scientist with a strong background in large-scale data analysis for machine learning applications to help build industry-leading Speech and Language technology. Our mission is to push the envelope in Automatic Speech Recognition, in order to provide the best-possible experience for our customers.

As a Data Scientist, you will work with talented peers to help the team advance the state of the art in spoken language understanding. Your work will directly impact our customers in the form of products and services that make use of speech and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in spoken language understanding.

Key job responsibilities

• Participate in the design, development, evaluation, deployment and updating of data-driven models and analytical solutions for ML and/or automatic speech recognition (ASR) applications.
• Apply statistical modeling techniques (e.g. Bayesian models or deep neural networks), optimization methods, and other ML techniques to different applications in business and engineering.
• Deep-dive into data to understand model failures and error pattern and to determine mitigation.

Basic Qualifications

• Solid programming skills and comfortable working with Linux command line.
• Scientific thinking and strong analytical skills.
• Strong written and spoken communication skills.
• Experience with scientific data analysis and/or modeling.

Preferred Qualifications

• PhD in Electrical Engineering, Computer Sciences, or Mathematics with specialization in speech recognition, natural language processing, or machine learning.
• Experience working with large datasets, conducting statistical analyses and creating data visualizations.
• Experience in building speech recognition and natural language processing systems.
• Experience working with natural language data (text or speech analysis).
• Knowledge of advanced machine learning techniques (deep learning and neural networks).
• Experience with Python.