The Staff Pad
This is a remote position.
Director, AI & Data Technologies Location : Helena, MT (Remote)
The Staff Pad has partnered with a leading healthcare organization in Helena, Montana to hire a Director of AI and Data Technologies. This senior leader will establish and oversee the enterprise-wide AI and data strategy, ensuring the organization leverages cutting‑edge technologies to advance clinical care, operational efficiency, and decision‑making. The Director will build and guide high‑performing AI, analytics, and data engineering teams, while shaping a strong data‑driven culture across the enterprise.
Position Overview The Director of AI & Data Technologies leads the organization’s AI, machine learning, and data strategy, driving innovation and ensuring responsible, secure, and effective use of data assets. This role oversees AI/ML development, modern data architecture, data governance, and enterprise‑wide adoption of emerging technologies that support business transformation and improved outcomes.
Key Responsibilities Strategy & Leadership
Establish and maintain an industry‑standard AI and data framework.
Develop the enterprise AI and data strategy, roadmap, and measurable outcomes.
Lead, mentor, and grow teams across analytics, business intelligence, machine learning engineering, and data engineering.
Promote a data‑driven culture through organization‑wide education, literacy, and responsible AI practices.
Collaborate with executives, cross‑functional leaders, and vendor partners to embed AI and data insights into business operations and digital transformation initiatives.
Technical Oversight & Implementation
Oversee the development, deployment, and monitoring of AI/ML models, including generative AI, predictive analytics, and deep learning solutions.
Provide technical direction on scalable data architecture, including data lakes, data warehouses, ETL pipelines, and cloud‑based systems.
Drive innovation by identifying and introducing new AI/ML technologies, platforms, and opportunities for competitive advantage.
Implement best practices for MLOps, DataOps, and model governance to ensure reliability, accuracy, and scalability of production systems.
Governance & Ethics
Lead data governance to ensure data quality, security, integrity, and availability.
Ensure ethical and responsible AI use, including bias mitigation, transparency, and explainability.
Oversee compliance with data privacy laws and emerging AI regulatory frameworks (GDPR, CCPA, etc.).
Identify and manage risks related to AI, data operations, security, and regulatory obligations.
Required Knowledge & Experience Technical Expertise
Advanced knowledge of AI/ML, deep learning, statistical modeling, and algorithms.
Proficiency with Python, R, and modern AI frameworks (PyTorch, TensorFlow, etc.).
Experience with cloud AI and data platforms (AWS, Azure, GCP).
Strong understanding of data engineering, ETL pipelines, data warehousing, and big data technologies (Spark, Snowflake, etc.).
Education
Bachelor’s or Master’s degree in Data Science, Computer Science, Engineering, AI, or related quantitative field required.
PhD preferred for highly technical leadership roles.
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Director, AI & Data Technologies Location : Helena, MT (Remote)
The Staff Pad has partnered with a leading healthcare organization in Helena, Montana to hire a Director of AI and Data Technologies. This senior leader will establish and oversee the enterprise-wide AI and data strategy, ensuring the organization leverages cutting‑edge technologies to advance clinical care, operational efficiency, and decision‑making. The Director will build and guide high‑performing AI, analytics, and data engineering teams, while shaping a strong data‑driven culture across the enterprise.
Position Overview The Director of AI & Data Technologies leads the organization’s AI, machine learning, and data strategy, driving innovation and ensuring responsible, secure, and effective use of data assets. This role oversees AI/ML development, modern data architecture, data governance, and enterprise‑wide adoption of emerging technologies that support business transformation and improved outcomes.
Key Responsibilities Strategy & Leadership
Establish and maintain an industry‑standard AI and data framework.
Develop the enterprise AI and data strategy, roadmap, and measurable outcomes.
Lead, mentor, and grow teams across analytics, business intelligence, machine learning engineering, and data engineering.
Promote a data‑driven culture through organization‑wide education, literacy, and responsible AI practices.
Collaborate with executives, cross‑functional leaders, and vendor partners to embed AI and data insights into business operations and digital transformation initiatives.
Technical Oversight & Implementation
Oversee the development, deployment, and monitoring of AI/ML models, including generative AI, predictive analytics, and deep learning solutions.
Provide technical direction on scalable data architecture, including data lakes, data warehouses, ETL pipelines, and cloud‑based systems.
Drive innovation by identifying and introducing new AI/ML technologies, platforms, and opportunities for competitive advantage.
Implement best practices for MLOps, DataOps, and model governance to ensure reliability, accuracy, and scalability of production systems.
Governance & Ethics
Lead data governance to ensure data quality, security, integrity, and availability.
Ensure ethical and responsible AI use, including bias mitigation, transparency, and explainability.
Oversee compliance with data privacy laws and emerging AI regulatory frameworks (GDPR, CCPA, etc.).
Identify and manage risks related to AI, data operations, security, and regulatory obligations.
Required Knowledge & Experience Technical Expertise
Advanced knowledge of AI/ML, deep learning, statistical modeling, and algorithms.
Proficiency with Python, R, and modern AI frameworks (PyTorch, TensorFlow, etc.).
Experience with cloud AI and data platforms (AWS, Azure, GCP).
Strong understanding of data engineering, ETL pipelines, data warehousing, and big data technologies (Spark, Snowflake, etc.).
Education
Bachelor’s or Master’s degree in Data Science, Computer Science, Engineering, AI, or related quantitative field required.
PhD preferred for highly technical leadership roles.
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