Amazon strives to be Earth’s most customer-centric company, where customers can find and discover anything they might want to buy online. By giving customers more of what they want - low prices, vast selection, and convenience - Amazon continues to grow and evolve as a world-class e-commerce website. Core to Amazon’s mission to delight and serve customers is a need to invent on behalf of vendors. Our team is at the forefront of two pivotal programs, EU AVS and WW VX, each integral to enhancing the end Customer Experience and contributing to Amazon’s Long-Term Free Cash Flow. The EU AVS program aims to provide an industry-leading account management service at the optimal cost-to-serve for Amazon that exceeds vendors’ expectations and expedites their growth on Amazon. The WW VX program vision is to make Amazon the most preferred, trusted, and efficient distribution option for vendors by building an industry-leading experience for every vendor across all global touchpoints.

Key job responsibilities
Our team is looking for an experienced Senior Business Intelligence Engineer with experience in quantitative analysis, econometrics, applied statistics, and/or machine learning to dive deep into business problems, detect vendor’s paint points and measure their impact on their engagement with Amazon. This role will help execute a long-term vision of data-driven Vendor Experience analysis through data exploration, correlation analysis, benchmarking and survey analysis. Output will be used by various teams including finance ops, supply chain, support to improve vendor’s experience and their ability to partner with Amazon. We are particularly interested in candidates with a research background in econometrics, data science, quantitative analysis, causal inference or some combination of these fields. However, we want to talk with any experienced professional with an interest in working on innovative, strategic problems with significant business impact. A successful candidate will be able to partner effectively with both business and technical teams, including clear communication of results and the ability to influence a variety of stakeholders. He/she will be an expert in manipulating large data sets and running experiments to validate developed approaches.

A day in the life
* Deep dives into vendor segmentation, behavior and satisfaction
* Leverage techniques from econometrics, computer science and statistics to measure vendor experience and its impact on their engagement and economics
* Drive development of tools, reporting improvements, and automation, and create new innovative and insightful reports.
* Support the functional teams with ad hoc data requests and analytical needs. * Partner with other science leaders throughout Amazon to effective solutions.

About the team
The AVS and VX program teams are diverse organizations with employees across Europe and with partner teams around the globe. This role can be based in London, Paris, Madrid, or Luxembourg. These teams drive improvements in products, services, tools, processes, communication, and vendor education world-wide working with partner teams in Europe, North America, Japan, and emerging locales and are responsible for all elements of a vendor’s interaction with Amazon including listing, catalog management, ordering, supply chain, marketing, payments, value-added services, and vendor support.

We are open to hiring candidates to work out of one of the following locations:

London, GBR

BASIC QUALIFICATIONS

* Degree in Engineering, Finance, Computer Science or a related technical field.
* Minimum of 5 years of relevant experience in advanced data analysis, applied data science or a related field.
* Solid analysis and econometrics skills.
* Solid experience working with large/disparate data sets, and with experimental design using data analysis languages (e.g., SQL, Python, Spark, etc.).

PREFERRED QUALIFICATIONS

* Phd in econometrics.
* 10 years experience in data analytics.
* Strong organizational and multitasking skills with ability to balance competing priorities.
* Comfort dealing with ambiguity.
* Ability to work effectively within an interdisciplinary science team of economists, applied scientists, software engineers, and data engineers.
* Excellent verbal and written communication skills with the ability to effectively advocate technical solutions to non-technical audience.