Description

Are you interested in using data and science to solve the largest scale problems in AWS Data Center Global Operations? Do you want to play a critical role in developing the future of repair in Data Center Operations through Machine Learning? Come join us!

The Central Infrastructure Analytics Team (CIAT) Data Scientist II transforms data into actionable insights for global teams by 1) interpreting enterprise scale data sets from a variety of internal sources to uncover the functional activity and implications, 2) analyzing this data to discover patterns, trends and correlations, 3) developing hypotheses and assisting in the design of experiments to explore these hypotheses, and 4) developing and deploying actionable ML models and business intelligence solutions for global customers.

CIAT collects data from diverse sources of internal systems which often require cleaning, interpretation, and combination in order to tell a functional story. The Data Scientist II role is critical in transitioning the analysis output from Descriptive/Diagnostic to Predictive/Prescriptive, and providing the operations teams with actionable insights to enable ongoing improvements. The Data Scientist II will use a variety of tools (e.g. Python, SQL, SageMaker, R, SAS, etc.) to deep dive data sources to discover useful patterns that will drive process improvement or remediate systemic issues.

AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help.

You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.

Key job responsibilities

• Design, develop, and evaluate innovative ML models to solve diverse challenges and opportunities across data center global operations

• Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity.

• Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production.

• Work with a scientists and software engineers to deliver machine-learning and data science solutions to production.

• Perform hands-on data analysis, employ statistical testing methods and strategies, run regular A/B tests, and clearly communicate the impact to technical and non-technical audiences in senior leadership.

• Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.

About the team

Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

We are open to hiring candidates to work out of one of the following locations:

Herndon, VA, USA | Seattle, WA, USA

Basic Qualifications

• 2+ years of data scientist experience

• 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience

• 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience

• Experience applying theoretical models in an applied environment

Preferred Qualifications

• Experience in Python, Perl, or another scripting language

• Experience in a ML or data scientist role with a large technology company

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 $125,500/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.