Data Science Lead
Listed on 2026-09-05
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IT/Tech
Data Analyst, Data Science Manager, Data Scientist, AI Engineer (Applied/Software)
Posting Information Posting Number
PG194783EP
Internal RecruitmentNo
Working TitleData Science Lead
Anticipated Hiring RangeCommensurate with education and experience ($110,000-$122,000)
Work ScheduleMonday through Friday, 8 am to 5 pm (additional work outside of standard hours may be required due to business needs)
DepartmentUniversity Data and Analytics
About the DepartmentUniversity Data and Analytics ( UDA ) is NC State’s institutional research office and the responsible unit for university-level data and analytics.
UDA is committed to:
- Empowering leaders and decision makers with the accurate, timely, and actionable information needed to advance the university’s mission;
- Maximizing the value and availability of institutional data resources for the broader NC State community; and
- Providing NC State’s stakeholders, partners, and external organizations with official university data.
Perks and Benefits
As a Pack member,
you belong here, and can enjoy exclusive perks designed to enhance your personal and professional well-being. As you consider this opportunity, we encourage you to review our Employee Value Proposition and learn more about what makes NC State the best place to learn and work for everyone.
Attain Work-life balance with our Childcare benefits,
Wellness & Recreation Membership , and Wellness Programs that aim to build a thriving wolfpack community.
Disclaimer:
Perks and Benefit eligibility is based on Part-Time or Full-Time Employment status. Eligibility and Employer Sponsored Plans can be found within each of the links offered.
The Data Science Lead will play a pivotal role in advancing NC State’s data and analytics capabilities. Applying advanced analytical and statistical techniques, methods, and tools, this role will develop and implement predictive models and other sophisticated analytics solutions. Working within University Data and Analytics ( UDA ), the Data Science Lead oversees a specialized team of up to three data scientists dedicated to developing and delivering analytical products and services that provide actionable insights, drive strategic decision-making, and enhance overall institutional effectiveness.
As the Data Science Lead, you will oversee a small team of data scientists responsible for developing advanced analytical solutions that support institutional planning and decision-making at NC State. You will apply statistical methods, predictive modeling, artificial intelligence, and machine learning to analyze complex university data and address institutional needs and uncover insights that support better outcomes. Additionally, you will coordinate data science projects, collaborate with partners across University Data and Analytics ( UDA ), and provide day‑time leadership and supervision of the Data Science team.
KeyImpact Areas include:
- Develop Advanced Analytics Solutions: Design, develop, and optimize predictive models, artificial intelligence and machine learning solutions, and other advanced analytics to address university needs and support institutional decision-making.
- Supervise and Support the Data Science Team: Provide day‑time supervision and leadership for the Data Science team, including coordinating work assignments, setting team priorities, coaching and developing staff, managing performance, and supporting a collaborative environment focused on continuous improvement and high‑quality work.
- Collaborate Across UDA : Partner with Institutional Reporting, Research and Analysis, Business Intelligence, Data Governance, UDA leadership, and other stakeholders to provide data science expertise and support cross‑functional initiatives.
- Coordinate Data Science Projects: Coordinate the execution of data science initiatives by tracking project progress, facilitating collaboration among stakeholders, managing project timelines and risks, and supporting alignment with UDA and institutional priorities.
- Support Responsible and Reliable Data Science Practices: Apply appropriate practices for model development and evaluation, data governance, security, privacy, and ethical use to support accurate, reliable, and responsible analytical solutions.
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