Data Scientist, Campaign Measurement & Optimization

Key Skills

Java Programming, Python Programming, C++, SQL, R Programming

Job Description

Job summary

Do you have a passion for diving deep to uncover key insights that drive critical business decisions? If yes, the Campaign Measurement & Optimization(CMO) team is looking for somebody with your enthusiasm and skills to work as part of the team. We are looking for an experienced data scientist

who is curious, driven, and passionate about marketing insights and analytics. If you are looking for a role where you can make a major impact, we want to meet you.

This role will work closely with scientists and engineers to develop and run statistical models to understand customer behavior and how customers respond to Amazon’s marketing. You will collaborate directly with economists, scientists to produce modeling solutions, partner with software developers and data engineers to build end-to-end data pipelines and production code, and have exposure to senior leadership as we communicate results and provide scientific guidance to the business. You will analyze large amounts of business data, automate, and scale the analysis, and develop metrics that will enable us to continually delight our customers worldwide.

As a successful data scientist, you are an analytical problem solver who enjoys diving into data, is excited about investigations and algorithms, can multi-task, and can credibly interface between technical teams and business stakeholders. Your analytical abilities, business understanding, and technical savvy will be used to identify specific and actionable opportunities to solve existing business problems and look around corners for future opportunities.

Responsibilities Include:

• Build models and tools using technical knowledge in machine learning, statistical modeling, probability and decision theory, and other quantitative techniques.
• Understand the business reality behind large sets of data and develop meaningful analytic solutions.
• Innovate by adapting to new modeling techniques and procedures.
• Utilizing code (Python, R, etc.) for analyzing data and building statistical models to solve specific business problems
• Improve upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters
• Collaborate with researchers, software developers, and business leaders to define product requirements and provide analytical support
• Communicating verbally and in writing to business customers and leadership team with various levels of technical knowledge, educating them about our systems, as well as sharing insights and recommendations