Data Scientist

Job description

DESCRIPTION

The Alexa Skills Science team uses data to inform the most critical strategic business decisions that impact how customers engage with Alexa skills (i.e., voice apps). As a Data Scientist output from your research will directly influence the marketing and education teams that teach developers how to build and add new features to their Alexa skills, the teams that teach customers what Alexa skills are and how to use them, and the product teams that add new experiences for how customers can discover and engage with Alexa skills.

The ideal candidate will have an extensive background extracting insights from complex data sets. They will also be a strong communicator, able to describe scientifically rigorous work to business stakeholders of varying levels of technical sophistication. They will be a partner to our business stakeholders, going beyond answering the question asked by pushing the business to consider new ways of examining its performance.

PREFERRED QUALIFICATIONS

· Master's degree or Ph.D. in Statistics, Mathematics, Engineering, Computer Science, or related analytical disciplines
· Ability to accurately determine cause and effect relationships
· Ability to communicate technical concepts and solutions at a level appropriate for technical and non-technical audiences
· Extensive experience applying theoretical models in an applied environment
· Previous experience in a ML or data scientist role with a large technology company
· Experience in developing machine-learning algorithms, statistical and mathematical optimization models, and simulation and visualization tools
· Personal interest in artificial intelligence, voice assistants, or natural language understanding

Amazon is an Equal Opportunity Employer – Minority / Women / Disability / Veteran / Gender Identity / Sexual Orientation / Age.

Desired profile

BASIC QUALIFICATIONS

· Bachelor's degree in quantitative field such as computer science, machine learning, mathematics, or statistics or equivalent experience
· 4+ years of experience with machine learning, statistical modeling, data mining, and analytics techniques
· Experience with R, Python, or other statistical/machine learning software
· Understanding of regression modeling, forecasting techniques, time series analysis, machine-learning concepts such as supervised and unsupervised learning, classification, random forest, etc.
· Experience developing experimental and analytic plans for data modeling processes and baselines
· Understanding of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc.
· Knowledge of SQL