Loading...
Machine Learning Scientist / Applied Scientist, EU Prime and Marketing Analytics & Science (PRIMAS)
Amazon
On-siteseniorPosted June 5, 2026
About the Role
Design and execute experiments for lifecycle marketing campaigns, build measurement frameworks, apply causal inference to determine incremental impact, and provide data-driven optimization recommendations.
Requirements
Seeks an Applied Scientist to design and execute rigorous experiments, build measurement frameworks, and apply causal inference methods to evaluate marketing campaign effectiveness.
Full Job Description
Are you interested in building the measurement foundation that proves whether targeted, cohort-based marketing actually changes customer behavior at Amazon scale?
We are seeking an Applied Scientist to own measurement and experimentation for our Lifecycle Marketing Experimentation roadmap within the PRIMAS (Prime & Marketing Analytics and Science) team. In this role, you will design and execute rigorous experiments that measure the effectiveness of audience-based marketing campaigns across multiple channels, providing the evidence that guides marketing strategy and investment decisions.
This is a high-impact role where you will build measurement frameworks from scratch, design experiments that isolate causal effects, and establish the experimental standards for lifecycle marketing across EU. You will work closely with business leaders and the senior science lead to answer critical questions: does targeting specific cohorts (Bargain hunters, Young adults) improve efficiency vs. broad campaigns? Which creative strategies drive behavior change? How should we optimize marketing spend across channels?
Key job responsibilities
Measurement & Experimentation Ownership:
1. Own measurement end-to-end for lifecycle marketing campaigns – design experiments (RCTs, geo-tests, audience holdouts) that measure campaign effectiveness across marketing channels
2. Build measurement frameworks and experimental best practices that work across different activation platforms and can scale to multiple campaigns
3. Establish experimental standards and tooling for lifecycle marketing, ensuring statistical rigor while balancing business constraints
Causal Inference & Analysis:
1. Apply causal inference methods to measure incremental impact of marketing campaigns vs. counterfactual
2. Navigate measurement challenges across different platforms (Meta attribution, LiveRamp, clean rooms, onsite tracking)
3. Analyze experiment results and provide optimization recommendations based on statistical evidence
4. Establish guardrails and success criteria for campaign evaluation
About the team
The PRIMAS team, is part of a larger tech tech team called WIMSI (WW Integrated Marketing Systems and Intelligence). WIMSI core mission is to accelerate marketing technology capabilities that enable de-averaged customer experiences across the marketing funnel: awareness, consideration, and conversion.
We are seeking an Applied Scientist to own measurement and experimentation for our Lifecycle Marketing Experimentation roadmap within the PRIMAS (Prime & Marketing Analytics and Science) team. In this role, you will design and execute rigorous experiments that measure the effectiveness of audience-based marketing campaigns across multiple channels, providing the evidence that guides marketing strategy and investment decisions.
This is a high-impact role where you will build measurement frameworks from scratch, design experiments that isolate causal effects, and establish the experimental standards for lifecycle marketing across EU. You will work closely with business leaders and the senior science lead to answer critical questions: does targeting specific cohorts (Bargain hunters, Young adults) improve efficiency vs. broad campaigns? Which creative strategies drive behavior change? How should we optimize marketing spend across channels?
Key job responsibilities
Measurement & Experimentation Ownership:
1. Own measurement end-to-end for lifecycle marketing campaigns – design experiments (RCTs, geo-tests, audience holdouts) that measure campaign effectiveness across marketing channels
2. Build measurement frameworks and experimental best practices that work across different activation platforms and can scale to multiple campaigns
3. Establish experimental standards and tooling for lifecycle marketing, ensuring statistical rigor while balancing business constraints
Causal Inference & Analysis:
1. Apply causal inference methods to measure incremental impact of marketing campaigns vs. counterfactual
2. Navigate measurement challenges across different platforms (Meta attribution, LiveRamp, clean rooms, onsite tracking)
3. Analyze experiment results and provide optimization recommendations based on statistical evidence
4. Establish guardrails and success criteria for campaign evaluation
About the team
The PRIMAS team, is part of a larger tech tech team called WIMSI (WW Integrated Marketing Systems and Intelligence). WIMSI core mission is to accelerate marketing technology capabilities that enable de-averaged customer experiences across the marketing funnel: awareness, consideration, and conversion.