Senior Economist, Marketing Measurements, Cmo Science

Details of the offer

Senior Economist, Marketing Measurements, CMO ScienceThe Campaign Measurement & Optimization (CMO) organization is looking for a Senior Economist interested in solving one of the most challenging business problems in marketing measurement and developing cutting-edge ML models. Working with our team of data scientists, applied scientists, research scientists, and economists, this leader will help redefine scalable marketing measurement at Amazon and its subsidiaries.

The CMO organization's mission is to be the most trusted source of measurement science solutions to drive marketing investment decisions across Amazon. The CMO team provides incrementality and efficiency measurement services to marketing stakeholders across Amazon's lines of business, including Stores, Prime Video, Amazon Devices, Alexa, Amazon Business, Amazon Music, Amazon Fresh, as well as subsidiaries including Audible, Ring, and Whole Foods. CMO applies industry-leading deep learning-based causal inference models to measure omni-channel effectiveness of marketing campaigns from these businesses worldwide. The impact and influence of the organization is tremendous, helping optimize spend decisions on a scale that exceeds many countries' GDP. Our outputs shape Amazon product and marketing teams' decisions and therefore how Amazon customers see, use, and value their experience with Amazon.

This is a high-impact role with opportunities to develop systems and analyze marketing effectiveness that contributes billions of dollars to the business. As a Senior Economist, you will be responsible for leading the design and development of cutting-edge measurement and optimization models, while collaborating with businesses, marketers, and software teams to solve key challenges facing the teams. Such challenges include measuring the incremental impact of multi-channel marketing portfolios, estimating the impact on sparse customer actions, and scaling measurement solutions for WW marketplaces. Unlike many companies that buy existing off-the-shelf marketing measurement systems, we are responsible for studying, designing, and building systems to serve Amazon's suite of businesses. Our team members have an opportunity to be on the forefront of marketing measurement thought leadership by working on some of the most difficult problems in the industry with some of the best product managers, scientists, economists, and software developers in the business.

In this role, you will be a technical leader in econometric research with significant scope, impact, and high visibility. You will lead strategic measurement science initiatives in CMO and across various marketing teams, scaling experimentation and development and deployment of measurement science models, real-time inference, and cross-channel orchestration. As a successful Economist, you are an analytical problem solver who enjoys diving into data, leading problem solving, guiding the development of new frameworks, writing code, and is excited about investigations and algorithms. You can credibly interface between technical teams and business stakeholders. You are an expert in causal inference models to solve business problems. You are a hands-on innovator who can contribute to advancing marketing measurement technology in a B2C and B2B environment, and push the limits on what's scientifically possible with a razor-sharp focus on measurable customer and business impact. You will also coach and guide scientists in the team to grow the team's talent and scale the impact of your work.
BASIC QUALIFICATIONS- PhD in economics or equivalent
- Experience in building statistical models using R, Python, STATA, or a related software
- 5+ years of relevant, broad research science experience after PhD degree or equivalent.
PREFERRED QUALIFICATIONS- Experience in developing and executing an analytic vision to solve business-relevant problems
- Experience in industry, consulting, government, or academic research
- Experience in implementing modern machine-learning methods (e.g., boosted regression trees, random forests, neural networks)
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

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