Amazon’s High Value Message (HVM) Analytics team (a part of Customer Behavior Analytics) is looking for an Applied Scientist to build scalable analytical solutions. The team uses Machine Learning and Causal Inference methods to measure how marketing campaigns impact customer perceptions.
The Customer Behavior Analytics (CBA) organization owns Amazon’s insights pipeline, from data collection to deep analytics. We aspire to be the place where Amazon teams come for answers, a trusted source for data and insights that empower our systems and business leaders to make better decisions. Our outputs shape Amazon product and marketing teams’ decisions and thus how Amazon customers see, use, and value their experience.
A successful candidate has an entrepreneurial spirit and wants to make a big impact on Amazon shoppers. You will develop strong working relationships and thrive in a collaborative team environment. You will work closely with business leaders, scientists, and engineers to translate business and functional requirements into concrete deliverables, including the design, development, testing, and deployment of highly scalable distributed services.
As an Applied Scientist, you bring structure to ambiguous business problems and use science, logic, and practical experience to decompose them into straightforward, scalable solutions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems; you're interested in learning; and you acquire skills and expertise as needed.
Main responsibilities include:
· Design and build scalable analytic solutions using ML and causal inference models to measure the impact of marketing campaigns on customer perceptions
· Work closely with both business units and engineering teams to formulate measurement problems and associated technical solution strategies
· Support engineering teams to build tools and applications on our unique big data platform to efficiently generate and deploy insights into decision-making systems at Amazon
· Raise the bar on applications of machine learning for advertising measurement and optimization
· PhD or equivalent Master's Degree plus 4+ years of experience in CS, CE, ML or related field
· Experience programming in Java, C++, Python or related language
· Strong background in ML, statistics, science applications to business problems, big data, and/or econometrics
· Hands on experience with at least one of the following: Python, Spark, Jave, C++
· Experience working with engineers to productionize ML models (data acquisition, validation, ML training, vending outputs)
· PhD in Machine Learning, Mathematics, Economics, Engineering or Related Fields
· Experience with marketing measurement and/or building production level systems for causal inference
· Advanced proficiency with statistical modeling, experimental design, and machine learning algorithms
· Expertise in Bayesian computation
· Experience with Spark and AWS services including S3 and EMR
· Experience in python’s machine learning and data science stack (tensorflow/pytorch/mxnet, numpy, pandas, matplotlib, scikit-learn, etc)
· Ability to convey rigorous mathematical concepts and considerations to non-experts.
· Strong software development skills.