- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience programming with at least one software programming language
- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Are you interested in taking a front-seat in the innovative technology that powers Amazon’s award-winning Customer Service? If so, come join us!
We are part of the Worldwide Customer Service Capacity Planning (WWCP) organization that enables end-to-end customer service workforce planning across Amazon. WWCP’s North Star vision is to define and deliver timely human-assisted support to Amazon customers under contact demand and Labor supply volatility and optimizing the Customer Service (CS) network for customer experience, associate experience, and cost. To turn this vision into reality, we are investing heavily on a digital transformative journey developing a product that will make capacity planning hands-off-the-wheel experience leveraging scientific methodologies and optimization techniques. Our ultimate objective is to establish a comprehensive, fully automated system capable of generating optimal plans on a massive scale. It will adapt seamlessly to fluctuations in supply and demand while maintaining our service-level (SL) goals. In addition to planning, the product will continuously monitor and manage real-time network performance, swiftly identifying emerging supply-demand gaps and ensuring the efficient utilization of flexible capacity through real-time network rebalancing
Why would you want to join our team?
If you are passionate about solving hard technical problems in the Optimization of Capacity Planning via Machine Learning and want your work to make an immediate impact in the real world, this is the place for you. We solve problems on par with leading academic research for the benefit of customers who celebrate our feature launches on social media, constantly demand new features, and - through adoption - force us to invent new ways to scale our systems. If going deep to optimize for scale, latency, and resource usage excites you as much as working backwards from the customer to develop features that not only work, but delight, then join us in making our product the most successful Worldwide capacity planning platform on the planet!
What does it take to succeed in this role?
In addition to meeting the technical qualifications, you need to be creative, responsible, and able to dig deep into emerging technologies. Willing to read research papers, but also move quickly to turn ideas into code that solves customer problems. A natural-problem solver, who is able to think about business problems, operational issues, and software architecture in the course of a single conversation. Curious about our customers' needs and dedicated to turning developers into raving fans. Excited to learn from others while bringing your own novel capabilities and perspectives. Someone who makes the team both productive and fun to work in.
About the team
WWCP is the world leader in providing cost-optimal solutions that enable customers to get outstanding human support, while raising the bar on associate experience. WWCP is responsible for: 1) Planning
customer support staffing. 2) Preserving customer experience when they contact customer service. 3) Ensuring best costs for providing customer support. WWCP crafts a comprehensive workforce management plan by strategically analyzing historical data and anticipating potential business events to accurately predicts the number of required associates for the specified period.
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