Data Science Engineer III- US

May 18

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Rackspace Technology

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Realize the full value of the cloud.

IT as a Service • Multi-Cloud • Managed Hosting • Managed AWS/Azure/Google Cloud Platform/OpenStack/Alibaba • Managed Private Cloud for VMware/Microsoft/OpenStack

5001 - 10000

Description

• As the AWS Data science Architect, you will be technically focused but also will understand and implement business planning. • Be the technical liaison between customers and engineering resources. • Provide tactical scope and work directly with the business representatives/customers to understand the requirements driving the need for a solution to be developed. • Communicate effectively with both business and technical colleagues throughout the course of the project • Ensure that all the appropriate questions are asked and verify that nothing crucial to the success of the project is overlooked • Be an AWS evangelist by educating a variety of customers on the value of AWS Machine Learning services • Work with customers to enable a DevOps culture and modernize operations and release strategies • Establish credibility and build impactful relationships with our customers to enable them to be Data Science and Machine learning advocates • Participate in deep architectural discussions to build confidence and ensure customer success when building new or migrating existing ML solutions onto AWS

Requirements

• 10+ years of experience in customer-facing software/technology, data analysis, or consulting • Minimum 5+ years of experience architecting and building Data Science and Machine Learning solutions • Minimum 5+ years of experience with AWS or other public cloud Data Science and Machine learning solutions • Proven experience in architecting and implementing data science and machine learning solutions on AWS • Experience in machine learning algorithms, statistics, data modeling techniques, and large language models • Professional experience with AWS Data Analytics and AI/ML Services • Demonstrated knowledge of software development tools and methodologies • Experience in Developing and implementing a variety of machine learning models, including but not limited to: Regression Models, Classification Models. Clustering Models, and Large Language Models • Lead the deployment of machine learning models, into production environments, ensuring seamless integration with existing systems and applications • Implemented and managed CI/CD pipelines for automated model deployment and updates • Solid understanding of agile methodologies • Master or Ph.D. in Computers and/or Data Science • AWS ML Specialization certification is a must

Benefits

• N/A