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# Applied Scientist, Amazon Digital Ads

- **Company:** Amazon.com, Inc.
- **Location:** Seattle, WA, United States
- **Experience:** Experienced
- **Salary:** $142,800.0 - $193,200.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Systems Engineering, Business Software, C++ (Programming Language), Data Mining, Distributed Systems, Python (Programming Language), Machine Learning, Parsing, Software Engineering, Reinforcement Learning, High Performance Computing, Optimization Algorithms
- **Published:** September 4, 2026
- **Apply:** https://www.jobmonkeyjobs.com/career/27994541/Applied-Scientist-Amazon-Digital-Ads-Washington-Seattle-7375

## About the Role

We are seeking a talented Applied Scientist to join our team and help us build innovative systems at the intersection of machine learning and causal inference. We develop new measurement and optimization tools that enable Amazon to make smart marketing investment decisions. This role will impact billions of dollars of decision-making by Amazon's most strategic businesses. Our most effective tools are released to external advertisers too, defining new industry standards. What makes us unique is our comprehensive data, our world-class engineering systems and a high concentration of some of the most talented scientists and engineers in industry.

As a successful candidate, you will be passionate about building scalable systems. You'll be comfortable with ambiguity and have exceptional technical acumen. You'll be up to speed on the latest research, and capable of developing new techniques at the intersection of causal inference, reinforcement learning and quantitative marketing. You will lead other scientists by example, with crisp technical writing and frequent presentations., 3+ years of building models for business application experience

 - PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
 - Experience programming in Java, C++, Python or related language
 - Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

Preferred Qualifications

 - Experience using Unix/Linux
 - Experience in professional software development

## Description

Build end-to-end causal machine learning solutions.

 - Perform hands-on analysis and modeling with enormous data sets to better understand how advertising influences shopper behavior.
 - Run A/B experiments that affect millions of customers to evaluate the impact of your solutions.
 - Spearhead new research agendas and own delivering on commitments.
 - Work closely with engineering to design systems that facilitate high velocity science exploration and quick prototype-to-prod timelines.
 - Develop novel methods at the intersection of causal inference, machine learning and quantitative marketing.
 - Present original research at internal and external conferences.

About the team
Our team is a dynamic mix of scientists who are passionate about innovating. We are excited to evaluate our novel causal models and optimization algorithms against ground truth generated by large-scale experiments. We think big, take risks and stay grounded.


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