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Data & AI Architect 206 views

IBM’s Data Science and AI Technology is a core part of their company’s strategy. IBM Data Science and AI are trailblazing new technology platforms and services, business models, and data scientist/developer outreach activities. They are pulling together a SWAT Team responsible for driving the initial engagement of their clients and deploying IBM Data and AI platform for any given client in their desired configuration and architecture.

In this role, you will provide technical leadership, design, and development for client engagements.

  • Keeps current on industry practices, regulations, technology, etc., and demonstrates technical knowledge in the area of responsibility
  • Builds networks/bridges with internal and external counterparts
  • Understand the challenges being addressed by an engagement and collaborate with the team and clients to deliver a technical solution that meets the unique needs.
  • Ability to look at results and tell stories to key stakeholders based on their analysis (need to have the ability to understand the data and its relationships)

Your Role & Responsibilities

  • Design, develop, construct, test and maintain data architectures and large-scale data processing solutions
  • Define the client architecture with IBM Data and AI platform integrated, operationalize the platform, and map relevant use cases for IBM Data and AI platform
  • Design and implement large scale data lakes using data virtualization best practices
  • Familiarity with a data science project’s life cycle from data understanding, preparation, model development, training, testing, scoring, and monitoring; including methods for measuring the effectiveness
  • Recommend and implement ways to improve data reliability, efficiency, and quality
  • Ensure that the architecture that is in place supports the requirements of the data stakeholders of the business
  • Leverage data from internal, external sources to answer business questions

Required Technical and Professional Expertise

  • Deep understanding of hybrid cloud architectures and data integration needs, and implementing solutions on multiple public and private clouds
  • Foundational OpenShift, dockers, containers
  • RedHat Linux admin, clustering
  • Familiarity with the Agile development process
  • 5+ experience with large-scale databases, Hadoop and/or Cloud-based data persistence
  • 5+ Design, develop and implement advanced data pipelines that bring together data from disparate sources, making it available to data analysts and other users using technologies like Kafka, Stream sets, Python Programming Language, etc.
  • 3+ years experience in open source Machine, and Deep Learning frameworks, model validation and deployment tools, data pipeline technologies, and visualization and data storytelling tools.

Preferred Technical And Professional Expertise

  • Experience implementing scalable data lakes in the cloud using cloud-based storage (Cloud Object Store)
  • Knowledge of RDBMS (Db2, Oracle, SQL Server) & ETL technologies (SSIS)
  • Experience creating & leveraging support best practices & process frameworks to drive continual process improvement
  • Ability to provide quality & testing support for all projects involving assigned applications
  • Experience with data modeling tools like SPSS, SAS
  • Experience implementing tools like Cognos, Tableau
  • Ability to design/implement governance strategies for data and ML models to provide trust and transparency Experience in machine learning, deep learning & programming
  • Statistical programming techniques & languages (e.g., R, Python, MATLAB, Java, etc )
  • Hands-on experience with common machine learning & data analysis packages
  • Experience in Natural Language Processing (NLTK)

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