DESCRIPTION

Are you passionate about building data driven solutions to solve a variety of problems in the cloud? Do you have a solid background in statistics, data analysis, and communication? Do you enjoy a fast-paced environment? If you answered yes to these questions, the EBS Data Science Team is a great place for you.

Amazon EBS (Elastic Block Store) is a virtualized storage service that offers highly available, high performance storage for EC2. As one of the core building block of AWS, EBS has experienced phenomenal growth since inception. This is a great opportunity to work on one of the most challenging problems in the cloud, with incredibly talented teammates who know how to ship. If you are passionate about large scale distributed systems, massive data analytics, or are interested in systems and kernel programming, then EBS is the perfect place for you.

The Data Science Team has made major contributions to a broad and strategic set of projects. These include design and launch of four new products, continuously monitoring and improving the entire product portfolio, and detailed modeling of customer usage patterns. Our team has a diverse background, including business, computer engineering, and genetics. We're very interested in candidates with a proven track record of rapidly solving problems with data.

As a Business Intelligence Engineer on the team you'll be working with a talented team to help understand and guide the business. We use a variety of data science tools, including SQL, Python, R, and Apache Spark. Our team is a mixture of software engineers and scientists who work together to build scalable solutions to important problems in cloud computing. Successful candidates will use data to drive improvements to the overall EBS business. Our team is composed of passionate, collaborative, deeply curious people who love to learn new things. The position is located in downtown Seattle, near several public transportation hubs.

About Us
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. Amazon's culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.
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.
This position involves on-call responsibilities, typically for one week every two months. We don't like getting paged in the middle of the night or on the weekend, so we work to ensure that our systems are fault tolerant. When we do get paged, we work together to resolve the root cause so that we don't get paged for the same issue twice.
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.

BASIC QUALIFICATIONS

• Degree in Math, CS, Operations Research or an interdisciplinary field that leverages statistics and programming
• High-quality communication skills.
• The ability to explain highly complex data sets and analyses with concise clarity.
• Experience in optimization, data analysis, and large scale simulations are all highly desirable.

PREFERRED QUALIFICATIONS

• Ph.D. degree in Math, CS, Operations Research or an interdisciplinary field that leverages statistics and programming
• High-quality communication skills.
• The ability to explain highly complex data sets and analyses with concise clarity.
• Experience in optimization, data analysis, and large scale simulations are all highly desirable.