Job description

  • Masters degree in Statistics, Applied Math, Operations Research, Economics, Computer Science, Engineering, or a related quantitative sciences field with 2+ years of relevant working experience, or a Bachelors degree with 5+ years of relevant working experience.
  • Proficient with data analysis and modeling software such as Spark, R etc.
  • Familiarity with programming languages such as C/C++, Python, Java or Perl.
  • Experienced in using multiple data science methodologies to solve complex business problems.
  • Experienced in handling large data sets using SQL and databases in a business environment.

Job summary
Amazon EC2 provides cloud computing which forms the foundation for the majority of AWS services, as well as a large portion of compute use cases for businesses and individuals around the world. A critical factor in the continued success of EC2 is the ability to provide reliable and cost effective computing. The EC2 Fleet Health and Lifecycle (EC2 FHL) organization is responsible for ensuring that the global EC2 server fleet continues to raise the bar for reliability, security, and efficiency. We are looking for seasoned engineering leaders with passion for technology and an entrepreneurial mindset. At Amazon, it is all about working hard, having fun and making history. If you are ready to make history, we want to hear from you!

Come join a brand new team, EC2 Health Analytics, under EC2 Foundational Technology, to solve complex cutting-edge problems to power a faster, more robust and performant EC2 of tomorrow. The charter of our team is to improve customer experience on the EC2 fleet by analyzing hundreds of signals and driving next-generation detection and remediation tools. We apply Machine Learning to predict outcomes and optimize decisions that improve customer experience and operational efficiency. As an Applied Scientist in the EC2 Health Analytics team, you will join an industry-leading engineering team solving challenging problems at massive scale.
  • Build a world-class forecasting platform that scales to handling billions of time series data in real time.
  • Drive fleet utilization improvement where each 1% means tens of millions of additional free cash flow.
  • Automate tactical and strategic capacity planning tools to optimize for service availability and infrastructure cost.
  • Build recommendation algorithms for improving the AWS customer experience.

  • Reduce dependence on manual troubleshooting for deep-dives.

What you will learn:
  • State-of-the-art analytics and forecasting methodologies.
  • Application of machine learning to large-scale data sets.

  • Product recommendation algorithms.
  • Resource management and admission control for the Cloud.
  • The internals of all AWS services.

Inclusive Team Culture
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences.

Work/Life Balance
Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.

Mentorship & Career Growth
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.

  • PhD degree in computer science, operations research, statistics, engineering, mathematics, or related technical field.
  • Experience with recommendation algorithms.
  • Experience with AWS products.
  • Experience with time-series forecasting.
  • Experienced in writing research papers.

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

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