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Senior Research Scientist, Automated Marketing and Events
1 month ago
Senior Research Scientist, Automated Marketing and Events We are looking for an inquisitive, lifelong learner with a keen interest in evidence-driven decision-making, e-commerce, digital businesses, and understanding customer behavior. We seek a researcher with an interest in the e-commerce industry and relevant experience to help evolve our off-site marketing experimentation frameworks. The ideal candidate will have a strong background in causal inference, experimental design, decision theory, and Bayesian statistics. This role aims to develop a new program that aims to be a leader in the industry, providing a unique opportunity for candidates to become experts in this fast-evolving domain. Our mission is to engage customers with the right products and services for a great shopping experience. You will play a key role in improving relevance for customers and optimizing Amazon's investments. The role involves working with cutting-edge technology and algorithms, including econometric methods, statistical modeling, machine learning, and data mining. Marketing is a significant driver of Amazon's business, offering a unique opportunity to impact the company's bottom line. You will also focus on developing novel A/B experimentation mechanisms to measure the effectiveness of machine learning solutions. Key job responsibilities: Design and build scalable analytic solutions using statistical models to measure the business impact of cross-channel marketing treatments. Collaborate with business units and engineering teams to formulate business problems into experimental designs and technical solutions. Develop a library of measurement solutions for data-driven decision-making. Contribute to the product roadmap with a focus on research and development to enhance bidding capabilities. Demonstrate superior verbal and written communication skills to convey mathematical concepts to non-experts. A day in the life: As a Senior Research Scientist, you will leverage your statistical and causal inference background to build the next generation of off-site marketing experimentation frameworks. This role requires a technically savvy leader capable of summarizing complex data and models through clear visual and written explanations. The ideal candidate will have experience in causal inference, experimental design, decision theory, Bayesian statistics, and building large-scale marketing experimentation frameworks. About the team: We are a team of scientists focused on building solutions in production. Our work involves prediction, optimization, and experimentation to provide data-driven insights for marketing decisions. We build scalable statistical frameworks and machine learning models to drive long-term profitability in the Automated Marketing and Events (AME) organization. Our key areas of focus include content selection, creation, moderation, bidding efficiency, and scalable experimentation frameworks for causal analysis. Minimum Requirements: PhD or Master's degree with 6+ years of experience applying scientific principles to business problems. Master's degree in a quantitative field such as engineering, technology, computer science, machine learning, statistics, or mathematics. Proficiency in R or Python. Advanced skills in statistical modeling, experimental design, and machine learning algorithms. Ability to research, evaluate, and implement modeling solutions for complex business problems. Experience communicating research findings to stakeholders across different levels of technical expertise. Preferred Qualifications: Experience translating research studies into practical changes. Familiarity with discrete and continuous optimization methodologies and algorithms. Amazon is an equal opportunity employer and is committed to diversity and inclusion in the workplace. The compensation for this position ranges from $143,300 to $247,600 per year, depending on geographic location and other factors. Amazon offers a comprehensive benefits package, including medical, financial, and other benefits. To apply, visit our career site. #J-18808-Ljbffr
