The EU Amazon Vendor Services (AVS) and WW Vendor Experience (VX) Program teams are looking for an experienced Applied Scientist (L6) to lead advanced causal inference and econometric modeling efforts that will drive critical business decisions and enhance our vendor experience.
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. 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. Both AVS and VX are core inputs to improving the end Customer Experience and Amazon's Long-Term Free Cash Flow.
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.
As a senior member of our data and analytics (DNA) team, you will play a crucial role in developing and implementing sophisticated causal inference models and econometric analyses to drive data-informed decisions across our organization. You will work closely with product managers, data scientists, and business stakeholders to deliver impactful insights that shape our vendor strategies and optimize our operations.
Key job responsibilities
- Develop advanced econometric and statistical models to rigorously evaluate the causal incremental impact of product feature releases.
- Develop approaches to understand the causal dependency between various business performance metrics.
- Estimate the incremental impact of actions designed to reduce vendor cost to serve.
- Own the end-to-end development of novel causal inference models that address the most pressing needs of our business stakeholders and help guide their future actions.
- Collaborate cross-functionally with marketing, product, data science, and engineering teams to define the measurement strategy and ensure alignment on objectives.
- Work with BIEs, data scientists, and product managers to automate models in production environments.
- Stay up-to-date with the latest research and methodological advancements in causal inference, causal ML, and experiment design to continuously enhance the team's capabilities.
- Effectively communicate analysis findings, recommendations, and their business implications to key stakeholders, including senior leadership.
- Mentor and guide colleagues, fostering a culture of analytical excellence and innovation.
BASIC QUALIFICATIONS
- PhD in Machine Learning, Econometrics, or a related field.
- 7+ years of experience in solving business problems.
- Experience applying causal inference techniques, such as double machine learning, synthetic control, difference-in-differences, instrumental variables.
- Experience with data scripting languages (e.g., SQL, Python, R, etc.).
- Expertise in SQL, data modeling, warehousing, and building ETL pipelines.
- Experience with AWS technologies (e.g., Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions).
- Knowledge of software engineering best practices and version control systems.
- Excellent ability to communicate with technical and nontechnical stakeholders alike in written documents and verbal communication to collect data requirements.
PREFERRED QUALIFICATIONS
- Experience in e-commerce or retail analytics.
- Track record of publishing research in top-tier conferences or journals.
- Experience working with product teams.
