The Amazon Web Services (AWS) Marketing Science team seeks an Applied Scientist with a strong background in machine learning and production level software engineering to spearhead the advancement and deployment of cutting-edge ML systems.
As part of this team, you will collaborate with talented peers to create scalable solutions to measure and optimize AWS events, advertising, and customer engagements to optimize investments, and inform decisions across marketing and sales.
You will work on high-impact, high-visibility products, with your work improving the experience of AWS leads and customers.
The ideal candidate possesses solid understanding of machine learning fundamentals, has experience writing high quality software in production setting, and experience or interest in causal inference and causal ML.
The candidate is self-motivated, thrives in ambiguous and fast-paced environments, possesses the drive to tackle complex challenges, swiftly delivering impactful solutions while iterating on science and user feedback, develops strong working relationships and thrives in a collaborative team environment.
Key job responsibilities
- Analyze, understand, and model customer behavior based on large scale data
- Lead the design, development, deployment, and innovation of advanced science models in the strategic area of marketing measurement and optimization
- Design, build, and deploy effective and innovative ML solutions to improve components of our ML and causal inference pipelines
- Build and deploy automated model training and evaluation pipelines
- Research and implement novel deep learning, reinforcement learning, and / or machine learning based algorithms to deliver insights on customer behavior
- Influence long-term science initiatives and mentor other scientists across AWS
BASIC QUALIFICATIONS
- 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
PREFERRED QUALIFICATIONS
- Experience building machine learning models or developing algorithms for business application
- Experience in professional software development
- Advanced proficiency with statistical modeling, experimental design, and machine learning algorithms
- Patents or publications at top-tier peer-reviewed conferences or journals
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