Sr. Data Scientist, Device Economics

Key Skills

Java Programming, Finance, Design, Python Programming, SQL, Deep Learning, R Programming, Terabyte scale datasets

Job Description

Amazon Devices has a rich set of subscription offerings, accessible on the wide array of devices Amazon creates. This leads to an array of tough business decisions, and the Subscription Sciences team within Device Economics is here to add scientific rigor to how those questions are answered. Leveraging existing science infrastructure and known techniques, you’ll focus both on combining estimates from existing models and creating new models and aggregating these results to produce business insights. You will own relationships with both the owners of the existing Science models and product owners for the subscriptions themselves. You will work to simplify, identifying where Science models overlap with each other and where we can align on a single methodology further upstream or reduce overlap. You will participate in multi-million dollar decisions leveraging your work and use the feedback from such decision making to help inform the roadmap so we keep all keep learning both as a team and as individuals in our careers.

A day in the life

Your day's will be split between working with scientists to refine and build models, and business leaders to interpret them. Always contributing to major decisions that can directly impact Amazon's bottom line on the order of multi-million dollar decisions.

About the team

• This role is in the Decision Science team, a are a cross-functional Consulting team within Device Economics that support's Amazon's Devices and Services teams that build hardware and software ranging from Kindle Paperwhite to Blink Video Camera subscriptions to FireTV OS to the Amazon's Astro robot.
• We own demand estimates and pricing recommendations for subscriptions and help inform critical decisions such as whether to invest or not, how to price them, etc. These decisions are made at the most senior levels of leadership.
• In practice, in addition to the primary job location on this job rec we are open to considering locations near major Amazon hubs including but not limited to Arlington VA (HQ2 near DC), Austin TX, Boston MA, Denver CO, Los Angeles CA, Seattle/Bellevue WA, San Diego CA.

BASIC QUALIFICATIONS

• Undergrad degree in Economics, Business, Finance, Engineering, Statistics, Computer Science, Mathematics, Supply Chain or related quantitative field
• 5+ years of work experience in a scientist or top down analytics role
• Experience with scripting and programming languages e.g. Python, SQL, R, etc. particularly around data manipulation
• Experience with statistical and machine learning models e.g. multinomial logistic regression, deep learning, etc.
• Comfort dealing with ambiguity
• Works backwards from the customer to solve their problems
• Excellent communication

PREFERRED QUALIFICATIONS

• Masters, MBA, or PhD degree in Economics, Business, Finance, Engineering, Statistics, Computer Science, Mathematics, or related quantitative field
• 8+ years of work experience in a scientist or top down analytics role
• 3+ years experience with scripting and programming languages e.g. Python, SQL, R, etc. particularly around data manipulation
• 3+ years experience with statistical and machine learning models e.g. multinomial logistic regression, deep learning, etc.
• Experience working with Data Scientists, Economists, Software Developers, and/or Product Managers
• Experience in Consumer facing Hardware or Services
• Experience in survey design and datasets