Senior Applied Scientist, Causal Inference, EU AVS/VX BIE team Job ID: 2868648 | Amazon EU SARL (UK Branch) 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.
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.
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Posted: January 8, 2025 (Updated 4 days ago) #J-18808-Ljbffr