The Networking Science team is looking for an exceptional Applied Scientist who is passionate about leveraging big data solutions for devising the next generation of network monitoring systems. Our mission is to develop models and tools to measure performance of AWS network. We deliver actionable insights across the Networking organization through descriptive analysis, data science, data engineering and ML/anomaly detection techniques.
The ideal candidate will share our excitement about the incredible opportunity cloud computing and Big Data analytics represent, and will be passionate about delivering high quality services. You will have good knowledge of distributed systems with design and implementation experience, as well as the ability to lead and mentor other engineers. Experience with databases, data warehousing, business intelligence, and machine learning are particularly valued, as is experience delivering large-scale big data services. You will be customer centric and enjoy working in a fast-paced environment that requires excellent technical and communication skills.
Networking Science team is based in Dublin, Ireland and Seattle, WA. You will join a tenured team of Research Scientists, Data Engineers and Software development engineers to lead the future of network availability and performance.
· Ph.D. MS, or equivalent in a discipline of science, mathematics, applied statistics, or similar.
· Several years of post-academic experience with quantitative statistics, including regressions, analysis of variance, multilevel models, structural equation models, or clustering techniques. You have a mastery or expert knowledge in at least one of these areas.
· Experience in predictive analytics, including supervised and unsupervised machine learning methods.
· Ability to deliver results with high autonomy and attention to details.
· Strong Customer focus, written and communication skills.
· Experience building and operating large-scale distributed systems in the cloud.
· Experience with industry standards big data technologies (Spark, Kafka, Hive, Presto, Airflow, etc).
· Experience working with and influencing key clients and stakeholders (internal or external).
· Experience converting ambiguous messy data into tangible actionable results.
· History of research publications and presentations.
· Meets/exceeds Amazon’s leadership principles requirements for this role
· Meets/exceeds Amazon’s functional/technical depth and complexity for this role
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.