Senior Economist, Amazon
1 month ago
The Global Cross-Channel and Cross- Category Marketing (XCM) org is seeking an experienced Economist to join our team. XCM’s mission is to be the most measurably effective and creatively breakthrough marketing organization in the world in order to strengthen the brand, grow the business, and reduce cost for Amazon overall. We achieve this through scaled campaigning in support of brands, categories, and audiences which aim to create the maximum incremental impact for Amazon as a whole by driving the Amazon flywheel.
This is a high impact role with the opportunities to lead the development of state-of-the-art, scalable models to measure the efficacy and effectiveness of a new marketing channel. In this critical role, you will leverage your deep expertise in causal inference to design and implement robust measurement frameworks that provide actionable insights to drive strategic business decisions.
Key Responsibilities:
- Develop advanced econometric and statistical models to rigorously evaluate the causal incremental impact of marketing campaigns on customer perception and customer behaviors.
- Collaborate cross-functionally with marketing, product, data science and engineering teams to define the measurement strategy and ensure alignment on objectives.
- Leverage large, complex datasets to uncover hidden patterns and trends, extracting meaningful insights that inform marketing optimization and investment decisions.
- Work with engineers, applied scientists and product managers to automate the model in production environment.
- 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 junior economists, fostering a culture of analytical excellence and innovation.
Qualifications:
- Experience applying causal inference techniques, such as double machine learning, synthetic control, difference-in-differences, instrumental variables, and randomized experiments.
- Proven track record of developing and implementing sophisticated, scalable models to measure marketing effectiveness and attribution.
- Expertise in programming languages (e.g., R, Python) and proficiency in working with large, complex datasets.
- Strong problem-solving skills, ability to think critically, and a keen eye for detail.
- Excellent communication and presentation skills, with the ability to translate technical analyses into actionable business insights.
- Experience in a fast-paced, data-driven environment, with the flexibility to adapt to changing business needs.
A day in the life:
- PhD in economics or equivalent.
- Experience in causal inference modelling.
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