Data Scientist- Alexa


Job Overview


Do you want to transform the way people enjoy video, music, & books? Come join the team that made Prime Music, Spotify, Pandora, Live Radio, Audible books, Kindle books, Podcasts, and more available to Alexa customers.

We are looking for a Data Scientist to join our team in the area of language modeling and research. We are seeking a customer-obsessed individual with strong modeling skills and technology experience to help us answer complex and exciting questions about how customers engage with Entertainment features on Alexa. In this role, you will work with a team of scientists, engineers, researchers, and product/program managers to build machine learning models that generate insights into customer interactions with Alexa and drive key business decisions.

A successful candidate is comfortable accessing and working with data from multiple sources, and can translate business requirements into the right modeling approach. They have a restlessness to answer “why?” questions and are passionate about using data to understand customer behavior and drive decision-making.

· Utilize code (Python, R, etc.) to build ML models to solve specific business problems
· Build and measure novel online & offline metrics for personal digital assistants and customer scenarios, on diverse devices and endpoints
· Research and implement novel machine learning algorithms and models.
· Collaborate with researchers, software developers, and business leaders to define product requirements and provide modeling solutions
· Communicate verbally and in writing to business customers and leadership team with various levels of technical knowledge, educating them about our systems, as well as sharing insights and recommendations


· Bachelor’s Degree
· 3+ years of experience with data scripting languages (e.g SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab)
· 2 years working as a Data Scientist


· Master’s degree or PhD in Statistics, Economics, Social Sciences, Computer Science, or related quantitative field.
· Multiple years of experience working with large-scale, complex datasets to create/optimize machine learning, predictive, forecasting, and/or optimization models.
· Strong proficiency in SQL
· 2+ years of relevant working experience in an analytical role involving data extraction, analysis, and communication
· Practical understanding and hands-on experience with regression modelling (linear and logistic)
· Excellent verbal and written communication skills with the ability to effectively advocate technical solutions to research scientists, engineering teams and business audiences
· Direct experience with both supervised learning methods (linear and logistic regression, time-series modelling, generalized linear models, decision trees, random forests, support vector machines, etc.) and unsupervised learning methods (K-means, hierarchical clustering, association rules, principal components).
· Proven ability to convey rigorous technical concepts and considerations to non-experts
· Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment

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