Sr. Manager, Applied Science, Marketing Measurement and Performance Science (MAPS)
Description
Amazon’s Customer Behavior Analytics org is seeking a Senior Manager, Applied Science, to lead the expansion of Marketing Measurement solutions. The team develops scalable ML and causal inference solutions to measure the effectiveness of Amazon’s marketing efforts and provides actionable insights to various marketing teams. This role impacts investments worth billions.
The team collaborates closely with business leaders, economists, product managers, and software teams to continuously improve strategic and operational planning. A successful candidate will be a self-starter, comfortable with ambiguity, and skilled in translating complex business challenges into scientific solutions.
Key job responsibilities
- Develop and implement large-scale ML and AI solutions to understand how Amazon’s marketing campaigns influence customer actions
- Lead the creation of advanced causal inference models to meet the critical needs of business stakeholders and guide their future actions
- Recruit and mentor high-performing economists, applied scientists, and business intelligence engineers
- Create and maintain team-building, planning, and review processes
- Evaluate and audit modeling processes and results from both internal and external team members
- Align the measurement plan with business strategy and formalize model assumptions
- Identify new research opportunities and bring a broad perspective to decision-making
About the team
The Customer Behavior Analytics (CBA) organization manages Amazon’s insights pipeline, from data collection to deep analytics. It aims to become a trusted source for data and insights that support better decision-making across Amazon teams and customers.
Basic Qualifications
- At least 10 years of experience building large-scale machine learning and AI solutions at Internet scale
- A Master's degree in Computer Science (Machine Learning, AI, Statistics, or equivalent)
- Experience building large-scale machine learning and AI solutions at Internet scale
- Ability to transform ambiguous business requirements into clear problem definitions and handle competing objectives
- Experience in recruiting and leading experienced scientists and developing junior members from academia or industry
Preferred Qualifications
- At least 10 years of practical experience applying ML to complex problems for large-scale applications
- 5+ years of hands-on experience with big data, machine learning, and predictive modeling
- 5+ years of experience in people management
- A PhD in Computer Science (Machine Learning, AI, Statistics, or equivalent)
- Experience in practical applications of ML to complex problems for large-scale applications
- Experience with big data technologies such as AWS, Hadoop, Spark, Pig, Hive
- Programming experience in Java, C++, or other languages, and proficiency in R, MATLAB, Python, or equivalent scripting languages
- Research experience in actual applications