Amazon Advertising operates at the intersection of eCommerce and advertising, offering a rich array of digital display advertising solutions with the goal of helping our customers find and discover anything they want to buy. We help advertisers reach Amazon customers on Amazon.com, across our other owned and operated sites, on other high quality sites across the web, and on millions of Kindles, tablets, and mobile devices. We start with the customer and work backwards in everything we do, including advertising. If you’re interested in joining a rapidly growing team working to build a unique, truly innovative advertising group with a relentless focus on the customer, you’ve come to the right place.
Our team, Machine Learning Optimization, develops machine learning algorithms in high performance, petabyte-scale distributed systems. Our systems process billions of ad impressions daily from across the internet to power all of Amazon’s advertising reporting, as well as algorithms for audience targeting, real time ad ranking and bidding, and automated campaign optimization.
We are looking for a talented Business Intelligence Engineer who is passionate about building metrics and pipelines and has the growth goal of getting deep in quantitative algorithm analysis. In this role, you will work with scientists, engineers, and product managers on high impact initiatives in Amazon’s Display Advertising.
· Innovate new machine learning approaches for advertising targeting and optimization
· Research and implement novel experimental design and measurement methodologies
· Establish scalable, efficient, automated processes for large scale machine learning
· Leverage petabyte scale data in strategic analysis for new monetization strategies, products and business directions
Impact and Career Growth:
· Identify problems and opportunities leading to significant business impact.
· Leverage petabyte scale data.
· Opportunity to grow and broaden your technical skills as you work in an environment that thrives on creativity, experimentation, and product innovation.
· Drive real-time algorithms to allocate billions of ads per day in advertising auctions.
· Have the ability to experiment effectively with meaningful projects.
Amazon is investing heavily in building a world class advertising business. Our products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities. Together, we will change the face of advertising and retail.
You can join our Seattle, New York or Boulder offices.
· PhD degree with 4 years of applied research experience or a Masters degree and 6+ years of experience of applied research experience
· 3+ years of experience of building machine learning models for business application
· Experience programming in Java, C++, Python or related language
· PhD or Masters in Computer Science, Statistics, or a related quantitative field with at least 5+ years of research experience in training and implementing advanced models (machine learning, predictive modeling, and analysis).
· 2+ years hands-on experience programming in R, Java, C#, C++ or other similar programming languages
· Algorithm and model development experience for large-scale applications
· Experience with digital media, online advertising or retail
· Good verbal and written communication and presentation skills, ability to convey mathematical concepts to non-experts
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 https://www.amazon.jobs/en/disability/us.