Sr. Manager, Applied Science, Marketing Measurement and Performance Science (MAPS)

Amazon
Seattle, WA, USA2026-01-20ONSITE

About the job

Amazon’s Customer Behavior Analytics org is looking for an Senior Manager, Applied Science, to spearhead the rapid growth of our Marketing Measurement solutions. The team focuses on building scalable ML and causal inference solutions to estimate the effectiveness of Amazon marketing efforts and provide actionable insights to the various marketing teams within Amazon. This is a high-impact role with opportunities to develop systems that affect investments to the size of billions of dollars. We work closely with business stakeholders and strive to continuously produce tangible impact on the company’s strategic and tactical planning and operations.

Responsibilities

Apply your expertise in ML/DL and statistical modeling to develop solutions and systems that describe how Amazon’s marketing campaigns impact customers’ actions

Own the end-to-end development of novel causal inference models that address the most pressing needs of our business stakeholders and help guide their future actions

Recruit high performing Economist, Applied Scientists and BIEs to the team and provide mentorship.

Establish team mechanisms, including team building, planning, and document reviews.

Review and audit modeling processes and results from scientists within and outside your team

Work with marketing leadership to align our measurement plan with business strategy

Formalize assumptions about how our models are expected to behave and explain why they are reasonable

Identify new opportunities that are suggested by the data insights - Bring a department-wide perspective into decision making

Qualifications

Minimum

10+ years of building large-scale machine learning and AI solutions at Internet scale experience

Master's degree in Computer Science (Machine Learning, AI, Statistics, or equivalent)

Experience building large-scale machine learning and AI solutions at Internet scale

Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives

Experience hiring and leading experienced scientists as well as having a successful record of developing junior members from academia or industry to a successful career track

Preferred

10+ years of practical work applying ML to solve complex problems for large-scale applications experience

5+ years of hands-on work in big data, machine learning and predictive modeling experience

5+ years of people management experience

PhD in Computer Science (Machine Learning, AI, Statistics, or equivalent)

Experience in practical work applying ML to solve complex problems for large scale applications

Experience working with big data, machine learning and predictive modeling

Experience in people management

Experience with big data technologies such as AWS, Hadoop, Spark, Pig, Hive etc.

Experience with Java, C++, or other programming language, as well as with R, MATLAB, Python, or an equivalent scripting language

Experience researching actual applications