Research Scientist

Have you ever thought about what it takes to deliver high quality customer service at optimal cost? What would you do to take one of the best customer service organizations in the world to the next level? Do you enjoy working in an entrepreneurial, fast paced environment, solving complex problems and delivering innovative and high-impactful solutions? Do you like to innovate and simplify?

The Worldwide Capacity Planning (WWCP) organization owns the end-to-end workforce planning and execution of Amazon's customer service network. Our forecasting, labor planning, scheduling, and real-time management solutions are responsible for the millions of daily decisions needed to provide efficient and frustration-free support to our customers around the world.

We are looking for an experienced Research Scientist with strong research background, excellent technical skills and business acumen to join our Science team.

Our science team is tasked with designing algorithms and systems for all stages of the labor planning process for Amazon customer service, from long-term headcount planning optimization, to short-term scheduling and real-time routing.

As a research scientist, you will work on cutting edge research using a combination of optimization, simulation, stochastic modeling, statistics, and/or machine learning to optimize one of the most complex service systems in the world.

You will interface with business leaders to understand the challenges we face on daily basis and present analysis and recommendations, using data-driven storytelling and influence to drive improvements in business operations and strategic change.

You will collaborate with software engineering, other data/research science, data engineering, and business leaders to develop, test and deploy a wide range of operation research and machine learning models. This is a highly impact role with goals that directly impact the bottom line of the business on a global scale.

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.

BASIC QUALIFICATIONS

- PhD, or Master's degree and 4+ years of quantitative field research experience

- Experience investigating the feasibility of applying scientific principles and concepts to business problems and products

- Experience with at least one modern language such as Java, Python, C++, or C# including object-oriented design

- Experience in designing, implementing, and testing analytic and/or algorithmic solutions to business or operational problems with a combination of operations research techniques including optimization, simulation, stochastic modeling, and data analytics.

PREFERRED QUALIFICATIONS

- Experience with various machine learning techniques and parameters that affect their performance

- Experience in patents or publications at top-tier peer-reviewed conferences or journals in operations research, statistics, and machine learning

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $212,800/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.

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