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Description

Drive the future of marketing measurement at Amazon by leading our experimentation and causal methods standards across a multi-billion dollar global marketing portfolio. In this role, you'll shape how Amazon evaluates and optimizes its marketing investments through innovative experimental design, rigorous causal analysis, and innovative applied Bayesian methods at scale to support in risk based marketing spend decision making. This role combines deep technical expertise with strategic impact, working at the intersection of advanced economic and statistical methods and billion-dollar business decisions.

The ideal candidate brings deep expertise in causal inference, experimental design, statistics, and Bayesian methods, with a passion for translating complex methodologies into actionable business insights. You'll have the opportunity to significantly impact how Amazon makes multi-billion dollar marketing decisions while advancing the field of marketing measurement science.

Join us in building the next generation of marketing measurement capabilities at Amazon.

Key job responsibilities

You'll collaborate with world-class scientists and business partners to:

-Pioneer new approaches to experimentation/RCT science, automation and scalability

-Establish and elevate experimentation standards across Amazon's marketing ecosystem

-Drive alignment on experimentation best practices across partner teams and the Amazon science community

-Lead the development of uncertainty quantification and risk-based decision-making frameworks

-Support scientists in designing and analyzing high-impact experiments

A day in the life

A sample day....9:00 AM: Review and provide scientific guidance on a complex experiment design for a $100M brand marketing campaign. Partner with measurement scientists to refine their uncertainty quantification approach and ensure alignment best in class scientific RCT standards.

11:00 AM: Lead a working session with cross-functional teams to evaluate a new experimentation framework that could improve Signal Utilization metrics across multiple marketing measurement models. Collaborate with data scientists to develop more robust calibration methods.

1:00 PM: Host office hours for embedded scientists across marketing teams, providing guidance on experimental design challenges and helping interpret experiment metrics for their specific business contexts.

2:30 PM: Partner with business stakeholders to translate experimental results into actionable insights, helping them understand the Expected Decision Value and potential regret of various marketing investment scenarios.

4:00 PM: Contribute to the development of new Bayesian methods for marketing measurement, focused on improving how we quantify and communicate uncertainty in marketing decision-making.

5:00 PM: Collaborate with executive science leaders to evolve experimentation standards and best practices, ensuring we're continuously raising the bar on marketing measurement across Amazon.

About the team

Our team helps powers the decision-making engine behind Amazon's global marketing investments, building state of the art measurement systems that determine where and how Amazon spends every marketing dollar. We combine advanced causal inference, experimentation, and machine learning to create a closed-loop marketing decision system that optimizes spend across brand and performance marketing. Our innovations in measurement science directly impact Amazon's growth, helping surface the most relevant ads to customers while maximizing marketing ROI. We're pioneering new approaches to marketing measurement that are setting industry standards and transforming how one of the world's largest advertisers makes marketing decisions.

Basic Qualifications

-PhD in Economics, Statistics, Computer Science, Marketing Science, or related quantitative field

-10+ years designing and analyzing experiments in an industry setting

-Experience with causal inference methods and uncertainty quantification

-Programming experience in Python, R, or similar statistical computing languages

-Published research or technical documentation on experimental methods or causal inference

-Experience mentoring or advising other scientists on experimental design and analysis

-Track record of collaborating with business stakeholders to drive data-driven decisions

-Experience developing statistical models for business applications

-Experience with Bayesian methods and probabilistic programming

Preferred Qualifications

Preferred qualifications include experience with large-scale marketing measurement, multiple experimental design methods (user, geo, item) including inventing new ones, and machine learning applications in causal inference. The ideal candidate will have a history of influencing scientific standards across organizations, presenting to executive audiences, and mentoring PhD-level scientists. Strong communication skills, business acumen, and the ability to drive clarity in complex situations are crucial for success in this high-impact role.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $170,500/year in our lowest geographic market up to $294,700/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.