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.