Job description

Title: Director of AI and Data Solutions Agency: VP DIGITAL TRANSFORMATION & TECHNOLOGY Location: Remote FLSA: Exempt Hiring Range: Full Time or Part Time: Additional Detail Job Description: As the Director of AI & Data Solutions at ODU, you will lead the strategic vision, development, and implementation of artificial intelligence, machine learning, data engineering, and data integration initiatives. You will play a key leadership role in transforming how data is used to inform decision-making, improve services, and enable intelligent automation across the university. This position requires strong cross-functional collaboration with IT, academic departments, institutional research, and external partners to deliver scalable and ethical data-driven solutions aligned with the university's goals. Minimum Qualifications: Master's Degree in Computer Science, AI, Data Science, Engineering, Information Systems, or a related field. Or a bachelor's in a related field with prior related work experience equivalent to a master's degree. • Strong programming skills in Python, R, SQL, or Java and experience with modern AI/ML frameworks (e.g., TensorFlow, PyTorch). • Deep understanding of data architecture, data modeling, pipelines, and warehousing in a complex IT environment. • Exceptional leadership, communication, and stakeholder engagement skills. • Experience with cloud platforms and services (e.g., AWS, Azure, Google Cloud), especially those used for AI and big data processing. • Hands-on experience with data integration tools such as Informatica, Boomi, Mulesoft, or equivalent. • Demonstrated experience in AI/ML solution development, data engineering, and enterprise-level data integration. • Flexibility to work outside of standard office hours as needed to support system implementations and upgrades. • Commitment to ongoing professional development in AI, machine learning, and data solutions. Additional Considerations: • A Ph.D. is preferred. • Experience working in a higher education or research-intensive environment. • Familiarity with enterprise data models and common higher education systems (e.g., SIS, LMS, CRM). • Experience implementing data lakes, lakehouses, or mesh architectures. • Certifications in AI/ML, cloud architecture, or data integration tools.

Requirements