Duke Staffing
Data architect
Duke Staffing, Denver, Colorado, United States, 80285
AI Strategy & Roadmap:
Collaborate with the Chief Data Officer and stakeholders to participate in the development and implementation of a comprehensive AI strategy that aligns with the organization's mission and objectives.Use Case Identification & Assessment:
Conduct thorough assessments of potential AI use cases, considering their feasibility, impact, and associated risks.Solution Review & Architecture:
Evaluate the technical soundness of AI project proposals, focusing on architecture, security, privacy, data quality, model performance, and scalability. Advise on design to ensure scalable and secure data architectures to support AI/ML workloads, ensuring data quality, availability, and compliance.Risk Management & Mitigation:
Assess the potential impact of AI projects. Identify and mitigate risks associated with AI projects, including data privacy concerns, algorithmic bias, and potential misuse of AI.Collaboration:
Foster strong relationships with cross-functional teams, including agency and OIT teams. Provide guidance and support on technical and ethical considerations and assist with strengthening procedure and operationalizing AI considerations.Technology Evaluation & Selection:
Stay abreast of the latest AI technologies and trends, evaluating their suitability for specific use cases and recommending appropriate solutions.Documentation:
Prepare clear and concise technical reports summarizing the findings of project reviews as well as outline trends in use cases and surface considerations around opportunities for future use.Required Skills and Experience:Leadership, communication and interpersonal skills, with the ability to translate complex technical concepts to diverse audiences on cross-functional teams.Technical background in AI and machine learning, including deep knowledge of AI/ML tools and models (e.g., Google Vertex, AWS Kendra, Snowflake Cortex, AWS SageMaker, Google AI Studio), cloud computing (i.e., AWS, Google Cloud Platform), big data technologies (i.e., Snowflake, Redshift, BigQuery), and data architecture principles.Experience with AI and data architecture and management.Knowledge of responsible AI principles and ethical considerations.Senior analytical and problem-solving skills.Additional Desired Skills and Experience:NIST AI Framework training or certification.
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Collaborate with the Chief Data Officer and stakeholders to participate in the development and implementation of a comprehensive AI strategy that aligns with the organization's mission and objectives.Use Case Identification & Assessment:
Conduct thorough assessments of potential AI use cases, considering their feasibility, impact, and associated risks.Solution Review & Architecture:
Evaluate the technical soundness of AI project proposals, focusing on architecture, security, privacy, data quality, model performance, and scalability. Advise on design to ensure scalable and secure data architectures to support AI/ML workloads, ensuring data quality, availability, and compliance.Risk Management & Mitigation:
Assess the potential impact of AI projects. Identify and mitigate risks associated with AI projects, including data privacy concerns, algorithmic bias, and potential misuse of AI.Collaboration:
Foster strong relationships with cross-functional teams, including agency and OIT teams. Provide guidance and support on technical and ethical considerations and assist with strengthening procedure and operationalizing AI considerations.Technology Evaluation & Selection:
Stay abreast of the latest AI technologies and trends, evaluating their suitability for specific use cases and recommending appropriate solutions.Documentation:
Prepare clear and concise technical reports summarizing the findings of project reviews as well as outline trends in use cases and surface considerations around opportunities for future use.Required Skills and Experience:Leadership, communication and interpersonal skills, with the ability to translate complex technical concepts to diverse audiences on cross-functional teams.Technical background in AI and machine learning, including deep knowledge of AI/ML tools and models (e.g., Google Vertex, AWS Kendra, Snowflake Cortex, AWS SageMaker, Google AI Studio), cloud computing (i.e., AWS, Google Cloud Platform), big data technologies (i.e., Snowflake, Redshift, BigQuery), and data architecture principles.Experience with AI and data architecture and management.Knowledge of responsible AI principles and ethical considerations.Senior analytical and problem-solving skills.Additional Desired Skills and Experience:NIST AI Framework training or certification.
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