Sr. Applied Scientist, AWS Data Center Infrastructure Operations
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) Sr. Applied Scientist 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 Applied Scientist 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 Applied Scientist 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.
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.
You will review key results with business leaders and stakeholders, and you will work with your team to develop and deploy a productionized version of the model to your global customers.
About the team
The Central Infrastructure Analytics Team (CIAT) provides critical business intelligence services across a broad range of functions within the AWS global Data Center Community (DCC). Situated within Central Operations, CIAT is the analytics hub for Data Center based organizations, including but not limited to: operations, logistics, engineering and equipment management, safety, and security.CIAT is comprised of several specialty Builder functions including data engineering, business intelligence (visualization), systems engineering, and data science. We build business intelligence solutions that drive the right actions at scale across our global data centers and supporting services.
Why AWS
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.
Inclusive Team Culture
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.
Work/Life Balance
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.
Mentorship and Career Growth
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.
Diverse Experiences
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.- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
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.
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.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/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.