Alexa is Amazon’s intelligent cloud-based voice recognition and natural language understanding virtual assistant. We’re building the speech and language solutions behind Amazon Alexa and other Amazon products and services. Come join our team and help improve the customer experience for the growing base of Alexa users!
As a Research Scientist in our Natural Understanding Central Analytics & Research Science team, you will be responsible for data-driven improvements and evaluation for our spoken language understanding models. You will be asked to design and create new customer value metrics impacting retention, satisfaction, engagement and to derive and describe customer segments to recommend opportunities to improve their Alexa experience. Your work will directly impact our customers in the form of products and services that make use of speech and language technology, particularly in developing predictive analytics models for user in continuously improving the Alexa experience for our customers.
· Build and release predictive models for retention and engagement using large datasets of user conversational behaviors and system performance to recommend and track the impact of feature improvements over time
· Ensure data quality throughout all stages of acquisition and processing, including such areas as data sourcing/collection, ground truth generation, normalization, and transformation.
· Collaborate with colleagues from science, engineering and business backgrounds.
· Present proposals and results to partner teams in a clear manner backed by data and coupled with actionable conclusions
· Define ML based techniques for sampling, judgment monitoring, A/B testing and efficient evaluations
· Work with engineers to develop efficient data querying infrastructure for both offline and online use cases
· PhD or equivalent Master's degree plus 4+ years of research experience in a quantitative filed
· Experience investigating the feasibility of applying scientific principals and concepts to business problems and products
· Bachelor’s degree in a relevant field, such as Computer Science, Applied Statistics, or Engineering
· 3+ years of experience with various machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance
· Experience in Perl, Python, or another scripting language; command line usage
· Experience analyzing data to identify patterns and conducting error/deviation analysis
· Knowledge of various machine learning techniques and key parameters that affect their performance
· Understanding of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc.
· Experience working with enterprise reporting systems, data analytics.
· Experience working as an Analytics Engineer or Data Scientist working with cross functional teams.
Amazon is an Equal Opportunity Employer – Minority / Women / Disability / Veteran / Gender Identity / Sexual Orientation / Age