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Senior Data Scientist, Alexa Audio Data and Insights

Job ID: 2608964 | Services LLC


Office locations include: Seattle WA, Bellevue WA, and Sunnyvale CA.

Amazon’s Alexa is a cloud-based voice service that powers Amazon’s groundbreaking voice-powered devices. These devices are part of Amazon’s vision to build a computer in the cloud that is completely controlled by your voice. Alexa Music is a critical Alexa domain, focused on delivering magical music experiences that drive adoption and engagement with Alexa.

The Alexa Audio Data and Insight (AUDI) team consists of talented Data Scientists, Business Intelligence Engineers, and Data Engineers. We seek an experienced Senior Data Scientist to drive Alexa Music customer engagement. You are the data science lead to define the ambiguous space. We are looking for a thought leader and you demonstrate this by delivering solutions, not just by having ideas. We encourage you to shape the business strategy with data driven recommendations. A successful candidate has an entrepreneurial spirit and wants to make a big impact on Alexa Music customers. You will develop strong working relationships and thrive in a collaborative team environment. Your role requires the ability to influence a team of contributors and interact with marketing executives. You draw from a broad data science expertise to mentor Scientists and Business Intelligence Engineers; following a rigorous scientific methodology, while providing leadership on complex technology issues. You provide guidance on cutting-edge methods in big data processing, data science literature, experimentation and careful consideration of modeling decisions. We expect you to have breadth of data science knowledge, familiar with casual inference and depth in predictive modeling (supervised learning) and A/B testing. In particular, this role would need in depth understanding and industry experience working with large datasets and building recommendation systems.

Problems we are solving include: 1) what music features should we proactively recommend to customers? 2) how should we prioritize content vs feature recommendations for the customers?

- Build/Develop/Apply existing models to support feature recommendations for customers
- Drive scientific best practices across teams mentoring others based on learnings gained through Alexa Audio's initiatives
- Proactively seek to identify business opportunities and provide solutions based on a broad and deep knowledge of Amazon’s data resources, industry best-practices, and work done by other teams.
- Partner with, coordinate, and influence multiple teams outside of Alexa Audio (Alexa Finance, Alexa Experience Data, Amazon Music, etc.), to support key initiatives.
- Be the voice of the customer (end customer and data consumer), aligning stakeholders with scalable mechanisms to incorporate our models into product and engineering decision-making processes

A day in the life
When we work together, we operate:

* Centralize the sprint and consolidate to one queue but still give stakeholder visibility and continue to ask feedback;
* Advocate knowledge sharing and code review;
* Avoid single point of failure with a secondary owner as code reviewer, mentor, backup, etc;
* Consolidate across org initiatives to the same primary owner;
* Train everyone on the must-have knowledges;
* Carve out time for high-sev tt, urgent requests, tech debt failure;
* Favor problem statement other than data requests

About the team
We are a team made up of Business Intelligence Engineers (BIEs), Data Engineers (DEs), and Data Scientists (DS’s), who bring with deep experience in both business analytics and data science. We cover the data needs of Music, Radio, Podcast, Books, and the Audio Category.

We are open to hiring candidates to work out of one of the following locations:

Bellevue, WA, USA | Seattle, WA, USA | Sunnyvale, CA, USA


- 7+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 5+ years of data scientist experience
- Experience with statistical models e.g. multinomial logistic regression


- Experience as a leader and mentor on a data science team

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $127,300/year in our lowest geographic market up to $247,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit This position will remain posted until filled. Applicants should apply via our internal or external career site.