Data science at scale at AWS

Building a predictive model or a data product in R is just the beginning. A successful model needs to be integrated into real-time production systems, tested and continuously monitored. Additionally, a newly created model entails data ingestion, processing and visualization. The output of the model needs to be securely shared and only authorized persons can access the results. And most importantly, can the model scale to infinity and beyond?

Speaker: Dzidas Martinaitis, data scientist @AWS

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We are supported by Amazon and they are hiring!

Senior/Lead Advanced Analytics Prototyping Developer: https://www.amazon.jobs/en/jobs/667333/senior-lead-advanced-analytics-prototyping-developer
ML Prototyping Architect: https://www.amazon.jobs/en/jobs/687065/ml-prototyping-architect
Senior Business Intelligence Engineer: https://www.amazon.jobs/en/jobs/681050/senior-business-intelligence-engineer
Data Analyst: https://www.amazon.jobs/en/jobs/665029/data-analyst-amazon-devices
Data Scientist: https://www.amazon.jobs/en/jobs/649487/data-scientist-kindle-content
Senior Data Scientist: https://www.amazon.jobs/en/jobs/680057/data-scientist-kindle-content

Please use Data Science Luxembourg or Dzidas Martinaitis for a reference in order to assure a support from Amazon in the future. If you have any questions regarding the roles fill free to email dzidoriu amazon.lu