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Senior Economist, Causal Inference, EU AVS/VX team

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Amazon

1mo ago

  • Job
    Full-time
    Senior Level
  • Data
    Research & Development
  • Berlin
    Remote

AI generated summary

  • You need a PhD in Economics, 5+ years in econometrics, causal inference techniques, SQL, AWS, and e-commerce analytics. Strong communication skills and a publishing record are essential.
  • You will develop causal models, analyze business metrics, collaborate with teams, automate processes, communicate findings, and mentor colleagues to drive analytical excellence.

Requirements

  • PhD in Economics, Econometrics, or a related field.
  • 5+ years in solving business problems through econometrics techniques.
  • 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.
  • Experience in e-commerce or retail analytics.
  • Track record of publishing research in top-tier conferences or journals.
  • Experience working with product teams.

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.

FAQs

What are the educational qualifications required for this position?

A PhD in Economics, Econometrics, or a related field is required for this position.

How many years of experience are needed for applicants?

Applicants should have 5+ years of experience in solving business problems through econometric techniques.

What causal inference techniques should applicants be familiar with?

Applicants should have experience applying techniques such as double machine learning, synthetic control, difference-in-differences, and instrumental variables.

What data scripting languages should candidates be proficient in?

Candidates should be proficient in data scripting languages such as SQL, Python, and R.

Is experience with AWS technologies necessary for this role?

Yes, experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions is required.

What communication skills are expected from candidates?

Candidates should possess excellent communication skills to engage with both technical and non-technical stakeholders in written documents and verbal communication.

Where can this position be based?

This position can be based in London, Paris, Madrid, or Luxembourg.

What is the primary role of the Senior Economist in the EU AVS/VX team?

The Senior Economist will lead advanced causal inference and econometric modeling efforts that drive critical business decisions and enhance vendor experience.

Are candidates expected to mentor others in this role?

Yes, the Senior Economist will mentor and guide colleagues, fostering a culture of analytical excellence and innovation.

Is prior experience in e-commerce or retail analytics preferred?

Yes, experience in e-commerce or retail analytics is preferred for this position.

Is there an emphasis on research publications for this role?

Yes, candidates with a track record of publishing research in top-tier conferences or journals will be favored.

What will be the main collaboration focus for this role?

The Senior Economist will collaborate across marketing, product, data science, and engineering teams to define measurement strategies and ensure alignment on objectives.

Can applicants with disabilities request accommodations during the hiring process?

Yes, applicants with disabilities can request accommodations during the application and hiring process. More information can be found on Amazon's website.

Retail & Consumer Goods
Industry
10,001+
Employees
1994
Founded Year

Mission & Purpose

Amazon is guided by four principles: customer obsession rather than competitor focus, passion for invention, commitment to operational excellence, and long-term thinking. We are driven by the excitement of building technologies, inventing products, and providing services that change lives. We embrace new ways of doing things, make decisions quickly, and are not afraid to fail. We have the scope and capabilities of a large company, and the spirit and heart of a small one. Together, Amazonians research and develop new technologies from Amazon Web Services to Alexa on behalf of our customers: shoppers, sellers, content creators, and developers around the world. Our mission is to be Earth's most customer-centric company. Our actions, goals, projects, programs, and inventions begin and end with the customer top of mind. You'll also hear us say that at Amazon, it's always "Day 1."​ What do we mean? That our approach remains the same as it was on Amazon's very first day - to make smart, fast decisions, stay nimble, invent, and focus on delighting our customers.