Sr Applied Scientist, Digital Ads , Amazon Digital Advertising

Amazon • Seattle, WA

1d • Onsite

About The Position

Amazon Advertising is seeking a Senior Applied Scientist to develop new systems and methods in challenging and data-rich areas of marketing. This role will leverage unique data, the latest machine learning methods, and big data technologies to understand how Amazon's marketing influences customer behavior. The position involves partnering with a dedicated engineering team to measure the impact of Amazon's marketing, identify optimization opportunities at scale, and build sophisticated decision engines. A major challenge is integrating petabyte-scale distributed retail systems into a singular service to synthesize e-commerce data into measurement and optimization models. The ideal candidate will have a background in causal inference, a start-up mentality, an appreciation for white-space, and success solving problems with large datasets.

Requirements

• 4+ years of building machine learning models for business application experience
• PhD, or Master's degree and 6+ years of applied research experience
• Experience programming in Java, C++, Python or related language
• Experience with neural deep learning methods and machine learning

Nice To Haves

• Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
• Experience with large scale distributed systems such as Hadoop, Spark etc.
• Knowledge of causal inference

Responsibilities

• Develop new techniques to process large data sets and contribute to the 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 to validate prototype models.
• Collaborate with scientists across teams in peer-review processes, publishing research in internal forums 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.

Benefits

• health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
• 401(k) matching
• paid time off
• parental leave
• sign-on payments
• restricted stock units (RSUs)

What This Job Offers

• Job Type: Full-time
• Career Level: Senior