Sr. Business Intelligence Engineer – Amazon Devices Customer Engagement

US-CA-Santa Monica
2 months ago
Job ID
Amazon Corporate LLC
Position Category
Business Intelligence

Job Description

Consider this challenge: every day, tens of millions of customers with unique interests and needs use Amazon devices as a part of their daily life. They might watch a video on their Fire TV, read a book on their Kindle, play a game on their Fire Tablet, and get a weather forecast from their Echo or any combination of thousands and thousands of other activities. We want to help every customer get more from the devices that they already own by providing them personalized content and recommendations across all of our device touchpoints. How do we do this in a way that puts the individual customer and their unique needs at the center of our communication across our varied devices?

In Devices Engagement we use state-of-the-art machine learning techniques, advanced customer segmentation/behavioral targeting and a relentless focus on device customer experience to answer this question. We are creating a new analytics team focused on building the analytical approach that will form the basis of our 1:1 communications with our millions of device owners. These approaches will range from from large-scale machine learning systems, to real-time, low-latency recommendation and ranking systems, building algorithms for understanding customer behavior and generating recommendations content, and automated measurement and testing approaches. You will work in a collaborative environment with our broader team of data and application engineers, product owners, designers and strategists. You will have a unique opportunity to create and build the programs that will drive direct, measurable impact to our customers, powering features on our devices used by millions and millions of customers every day.

About our team:
This team is brand new – created to gets things done to improve the customer experience and increase Amazon Device engagement. That means we have no technical debt and the freedom to take advantage of all the new tools and techniques available as we build out our machine learning and analytical capabilities. We refuse to accept constraints, internal or external, and have a strong bias for action. We love data and believe that we can use it to deliver epic experiences for our customers. We’re going to build epic stuff. This is your chance to “do it right” with virtually no constraints.

About you:
You want to make changes that help millions of customers. You don’t want to simply make something 10% better as a part of an enormous team, but rather you want to create and lead a team that will invent brand new stuff. You are a analytics professional with experience in recommendation systems, machine learning, big data and data science. You are passionate about customer experience and want to shape our customer and analytics strategy by taking a key leadership role in the Device Customer Engagement team. You have great problem solving skills. You love keeping abreast of the latest technology and use it to help you innovate. You have strong leadership qualities, great judgment, clear communication skills, and a track record of delivering great products.

Basic Qualifications

  • A Bachelor's degree in Economics, Math, Statistics or a related field is required.
  • 7+ years of customer analytics experience
  • Experience in using statistical analysis software packages (e.g. R, SQL)
  • Experience with Redshift, Netezza, Greenplum, Vertica or other Massively Parallel Processing (MPP) database platforms as well as Map Reduce frameworks such as Hive/Hadoop.
  • Experience building analytic services for production environments

Preferred Qualifications

  • Ability to communicate and discuss analytical concepts in simple, general terms with business partners and in great detail with software development engineers
  • Excellent problem solving skills
  • Excellent written and oral communication skills
  • Experience with customer 1:1 personalization solutions
  • Experience building operational ML models
  • Track record of delivering results in a collaborative work environment
  • High attention to detail and proven ability to manage multiple, competing priorities simultaneously
  • Composed, poised, and professional demeanor
  • Willingness to roll up one’s sleeves to get the job done
  • Well-timed tenacity and conviction
  • Ability to change directions when presented new data
  • Vocally self-critical is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation
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