Are you excited about working on large scale Natural Language Processing (NLP), Machine Learning (ML), and Deep Learning (DL)? We are embarking on a multi-year journey to improve the shopping experience for customers globally. This is a unique opportunity to build technology and science that millions of people will use every day. price changes, advertising strategy changes, introducing new selection etc.) as well as using this information to optimize our fee structure and maximizing our long term profitability. Within the Science team, our goal is to understand the impact of changing fees on Seller (supply) and Customers (demand) behavior (e.g. We own the fee strategy, fee seller experience, fee accuracy and integrity, fee science and analytics, and we provide scalable technology to monetize all services available to third-party sellers. If you are interested, please send your CV to our mailing list at About the team The Selling Partner Fees team owns the end-to-end fees experience for two million active third party sellers.
#AMAZON MOMENTS FULL#
Roughly 85% of previous cohorts have converted to full time scientist employment at Amazon. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement.
#AMAZON MOMENTS HOW TO#
You will learn how to build data sets and perform applied econometric analysis at Internet speed collaborating with economists, scientists, and product managers. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. Some knowledge of econometrics, as well as basic familiarity with Python is necessary, and experience with SQL and UNIX would be a plus. We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to work with large and complicated data sets.
About the team We are a multidisciplinary team that combines the talents of science and engineering to develop innovative solutions to make Amazon Earth's Best Employer. Our economists also collaborate with partner teams throughout the process, from understanding their challenges, to developing a research agenda that will address those challenges, to help them implement solutions.
#AMAZON MOMENTS CODE#
This might include identifying the appropriate research questions, writing code to implement a DID analysis or estimate a structural model, or writing and presenting a document with findings to business leaders. A day in the life Work with teammates to apply economic methods to business problems. Use scientifically rigorous methods to develop and recommend career paths for employees. Examine how external labor market and economic conditions impact Amazon's ability to hire and retain talent. Key job responsibilities Use causal inference methods to evaluate the impact of policies on employee outcomes. They will be customer-centric and will communicate scientific approaches and findings to business leaders, listening to and incorporate their feedback, and delivering successful scientific solutions. They will work closely with engineering teams to develop scalable data resources to support rapid insights, and take successful models and findings into production as new products and services. They will work with teammates to develop scientific models and conduct the data analysis, modeling, and experimentation that is necessary for estimating and validating models. Ideal candidates will work in a team setting with individuals from diverse disciplines and backgrounds.
We are looking for creative thinkers who can combine a strong technical economic toolbox with a desire to learn from other disciplines, and who know how to execute and deliver on big ideas as part of an interdisciplinary technical team. The ideal candidate will work with engineers and computer scientists to estimate models and algorithms on large scale data, design pilots and measure their impact, and transform successful prototypes into improved policies and programs at scale. We are looking for economists who are able to apply economic methods to address business problems. We are an interdisciplinary team that combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal.
The People eXperience and Technology Central Science Team (PXTCS) uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, wellbeing, and the value of work to Amazonians.
0 kommentar(er)
