Overview As a Scientist on the Sponsored Products and Brands team, you will advance methods to quantify how traffic sources, customer journeys, and onsite experiences influence purchasing and revenue. You will lead analyses that separate true business impact from mere correlation using experiments, causal inference, and ML, shaping products and investments. You'll translate complex findings into actionable recommendations and build tools to speed diagnosis and decision-making. This high-visibility role blends science leadership with hands-on delivery to improve measurement across Amazon Ads.
Compensation / Benefits- health insurance (medical, dental, vision)
- 401(k) matching
- paid time off
- parental leave
- RSUs and sign-on payments
- comprehensive benefits
Responsibilities- Develop methods to understand how traffic sources, customer journeys, and onsite experiences drive purchasing and revenue using experimentation, causal inference, and machine learning
- Lead or heavily influence the design of scientifically complex software solutions or systems and provide system-wide design guidance
- Define a long-term science vision and roadmap combining leadership, technical depth, and business understanding
- Translate complex findings into clear recommendations for product, engineering, and business partners and build tools for faster diagnosis and better investment decisions
- Mentor junior scientists, raise the scientific bar, and identify opportunities where generative AI can accelerate learning and efficiency
Key requirements- 3+ years of building ML models for business applications
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
- ability to communicate complex findings clearly to cross-functional partners
- mentorship and leadership of junior scientists
- strong collaboration across product, engineering, and business teams
- machine learning
- causal inference
- experimentation design
