The Alexa Feedback organization owns a number of programs and domains which drive high customer engagement and feature discovery, maintains customer trust, understands customers’ feedback, develops new features that provide utility value for customers with special needs, and develops locally relevant experiences. The Alexa Experience Science team applies machine learning and natural language understanding algorithms to improve these programs and the functionality of domains such as News (“Alexa, What's the news?"), Feedback (“Alexa, that was wrong!"), Personality (“Alexa, what’s your favorite color?”), and to advance Alexa’s ability to handle more ambiguous utterances.
We’re looking for a passionate, talented, and inventive Scientist to help build industry-leading ML technologies that help provide the best-possible experience for our customers. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to develop new features, predict key user behaviors and deliver automated decisions, both offline and in real time.
· PhD in highly quantitative field (CS, machine learning, mathematics, statistics) or equivalent experience.
· 5+ years of experience with machine learning, statistical modeling, data mining, and analytics techniques.
· Previous experience in a ML or data scientist role with a large technology company.
Ideal candidate profile
· PhD or equivalent Master's Degree plus 4+ years of experience in CS, CE, ML or related field
· 2+ years of experience of building machine learning models for business application
· Experience programming in Java, C++, Python or related language
· Bachelor or Master's degree in highly quantitative field (CS, machine learning, mathematics, statistics) or equivalent experience.
· Experience with R, Python, SAS, Matlab or other statistical/machine learning software.
· Experience applying various machine learning techniques, and understanding the key parameters that affect their performance.
· Experience developing experimental and analytic plans for data modeling processes, use of strong baselines, and the ability to accurately determine cause and effect relationships.
· Have a history of building systems that capture and utilize large data sets in order to quantify performance via metrics or KPIs.
· Understanding of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc.
Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation