Research Scientist, Amazon Customer Service
Amazon
DESCRIPTION
The Worldwide Capacity Planning (WWCP) team within Amazon Customer Service (CS) needs an innovative Research Scientist to help revolutionize how we deliver exceptional customer service at scale. Our team owns end-to-end workforce planning and execution for Amazon's global customer service network, developing the forecasting, scheduling, and real-time management solutions that power efficient, frustration-free customer support.
We are seeking an experienced Research Scientist with a strong research background, excellent technical skills, and business acumen to join our Science team. You will design algorithms and systems spanning the full spectrum of labor planning - from long-term headcount optimization to real-time routing - using advanced techniques in optimization, simulation, stochastic modeling, statistics, and machine learning.
In this role, you will:
- Partner with business leaders to understand operational challenges and drive strategic improvements through data-driven storytelling and analysis
- Collaborate across software engineering, data science, and business teams to develop and deploy innovative operations research and machine learning solutions
- Design and implement scalable algorithms that optimize complex service systems
- Lead research initiatives that directly impact the efficiency and quality of Amazon's worldwide customer service delivery
This high-impact position offers the opportunity to solve complex problems at global scale while working in a fast-paced, entrepreneurial environment focused on continuous innovation and simplification.
Key job responsibilities
- Design and develop advanced models with a combination of optimization, computer simulation, stochastic modeling, statistics, and/or machine learning techniques to create scalable solutions for business problems in customer service labor planning.
- Collaborate with product, software engineering, research science, data engineering, and business leaders to build appropriate business and technical solutions.
- Conduct research, prototype, and experiment with models and solutions using scripting languages such as Python. Participate in the production-level deployment of these solutions.
- Use the best practices in science: data integrity, design, test, and implementation and documentation.
- Contribute to Amazon's Intellectual Property through patents and internal and external publications.
- Mentor and guide junior members in the team.
A day in the life
We thrive on solving challenging problems to innovate for our customers. By pushing the boundaries of technology, we create unparalleled experiences that enable us to rapidly adapt in a dynamic environment. Our decisions are guided by data, and we collaborate with engineering, science, and product teams to foster an innovative learning environment.
If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!
Benefits summary:
Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include:
1. Medical, Dental, and Vision Coverage
2. Maternity and Parental Leave Options
3. Paid Time Off (PTO)
4. 401(k) Plan
About the team
Worldwide Capacity Planning optimizes capacity across operations sites that help minimize customer wait time and route customers to the associate who can best resolve their issue, on the first contact. We build forecasting models and optimization tools that help predict the hourly capacity requirement, including when there are new device or game launches, or when there is a special event, such as Prime Day.