Sr Applied Scientist, Digital Ads , Amazon Digital Advertising

Amazon.com Inc

Seattle, WA

JOB DETAILS
SKILLS
Advertising, Analysis Skills, Big Data, Business Growth, Conferences, Customer/Consumer Behavior, Data Analysis, Data Processing, Data Sets, Develop Methodologies, Distributed Computing, Econometrics, Industry Standards, Investment Services, Machine Learning, Marketing, Marketing Objectives, Model Validation, Problem Solving Skills, Product Engineering, Prototyping, Retail, Startup, Statistical Modeling, Statistics, Technical Marketing, eCommerce
LOCATION
Seattle, WA
POSTED
30+ days ago

Are you passionate about developing new state-of-the-art measurement approaches at Petabyte scale? Amazon Advertising is one of Amazon's fastest growing businesses, and we are leveraging our unique data, the latest machine learning methods and big data technologies to better understand how Amazon's marketing influences customer behavior. We are looking for a Senior Applied Scientist to develop new systems and methods in the most challenging and data rich areas of marketing. We need an expert in experimental statistics, machine learning or causal inference to design advanced new models with our world class data systems.

Dozens of Amazon businesses use Amazon's ad tech for their marketing objectives, driving more than $1B of marketing investments through Ads services and tools. As part of the 1PM team, this role will partner with a dedicated engineering team measuring the impact Amazon"s marketing and identifying opportunities for optimization at scale. We drive initiatives to make smarter marketing decisions and improve the relevance of advertising to our customers. We move away from industry standard measurement systems and build sophisticated and insightful decision engines. We enable massive advertising programs, generating billions of impressions decorated with rich representations of customer state. The major challenges we are solving include integrating petabyte-scale distributed retail systems into a singular service to synthesize e-commerce data into measurement and optimization models. The successful candidate will have a causal inference background, a start-up mentality, an appreciation for white-space, and success solving problems with large data sets.

Key job responsibilities

  • Scientists at Amazon are expected to develop new techniques to process large data sets and contribute to design of automated systems.
  • Apply ML, statistics or econometrics knowledge to develop and analyze prototype models.
  • Design and analyze data from large-scale online experiments in order to validate prototype models
  • Collaborate with scientists across teams in peer-review processes , publishing research in internal forms and industry conferences
  • Partner closely with product and engineering teams to develop new measurement systems and translate prototype models to production.
  • Establish scalable, efficient, and automated processes for large scale model development, validation, and implementation.
  • Research and experiment with novel statistical modeling approaches.

About the Company

A

Amazon.com Inc

At Amazon, we don’t wait for the next big idea to present itself. We envision the shape of impossible things and then we boldly make them reality. So far, this mindset has helped us achieve some incredible things. Let’s build new systems, challenge the status quo, and design the world we want to live in. We believe the work you do here will be the best work of your life.

Wherever you are in your career exploration, Amazon likely has an opportunity for you. Our research scientists and engineers shape the future of natural language understanding with Alexa. Fulfillment center associates around the globe send customer orders from our warehouses to doorsteps. Product managers set feature requirements, strategy, and marketing messages for brand new customer experiences. And as we grow, we’ll add jobs that haven’t been invented yet.

It’s Always Day 1
At Amazon, it’s always “Day 1.” Now, what does this mean and why does it matter? It means that our approach remains the same as it was on Amazon’s very first day – to make smart, fast decisions, stay nimble, invent, and stay focused on delighting our customers. In our 2016 shareholder letter, Amazon CEO Jeff Bezos shared his thoughts on how to keep up a Day 1 company mindset. “Staying in Day 1 requires you to experiment patiently, accept failures, plant seeds, protect saplings, and double down when you see customer delight,” he wrote. “A customer-obsessed culture best creates the conditions where all of that can happen.” You can read the full letter here

Our Leadership Principles
Our Leadership Principles help us keep a Day 1 mentality. They aren’t just a pretty inspirational wall hanging. Amazonians use them, every day, whether they’re discussing ideas for new projects, deciding on the best solution for a customer’s problem, or interviewing candidates. To read through our Leadership Principles from Customer Obsession to Bias for Action, visit https://www.amazon.jobs/principles
COMPANY SIZE
10,000 employees or more
INDUSTRY
Retail
FOUNDED
1994
WEBSITE
http://Amazon.com/militaryroles