Edtech.com's Summary

The University of Virginia is hiring The Stephenson Dean of the School of Data Science. The Dean will lead the School's growth and development, driving interdisciplinary research, academic excellence, and partnerships to position the School as a national and global leader in rigorous, responsible, and impactful data science and AI.

Highlights

Lead and develop the School's interdisciplinary identity in data science education, research, and societal engagement.
Guide academic programs, enrollment strategies, faculty and staff recruitment, and infrastructure growth.
Advance research breakthroughs and responsible application of data science, particularly in AI.
Strengthen collaborations within UVA and externally with industry, alumni, donors, and government partners.
Serve as chief academic and administrative officer, acting as ambassador and thought leader for the School.
Oversee fundraising and resource diversification to support scholarships, faculty excellence, and capital projects.
Require intellectual leadership with a strong record qualifying for full professor tenure or equivalent.
Expect experience in organizational leadership, financial management, and operational excellence.
Prioritize collaborative, community-oriented, entrepreneurial, and values-driven leadership styles.
Engage deeply with diverse stakeholders to foster inclusive, evidence-based decision-making for sustained impact.

The Stephenson Dean, School of Data Science Full Description

Position at a Glance

Prepared by Heidrick & Struggles for the University of Virginia (UVA) School of Data Science.

Position title: The Stephenson Dean, School of Data Science
Location: Charlottesville, Virginia
Reports to: Executive Vice President and Provost

The Opportunity

The University of Virginia (UVA) seeks a visionary, strategic, and entrepreneurial leader to serve as The Stephenson Dean of the School of Data Science.

The School of Data Science began as the University-wide data science institute and became UVA's 12th and newest school in 2019, through the largest private gift in University history. As the first standalone school of data science in the nation, the School of Data Science was designed to advance discovery, share knowledge, and apply data science for societal benefit.

The School of Data Science now stands at a natural transition point. Its next Dean will help articulate the School’s distinctive contribution to an evolving, interdisciplinary field—one that draws from statistics, computer science, mathematics, engineering, the social sciences and humanities, policy, and many areas of application—while continuing to strengthen the School’s academic identity, reputation, and connections across UVA. Central to this identity is an approach to data science grounded in technical rigor, informed judgment, and meaningful societal impact.

The next Dean will build on the openness and interdisciplinary character that have defined the School from the beginning. The Dean will help the School respond to rapid advances in AI and other data-intensive methods while reinforcing data science's foundational role in the development and responsible application of AI. The role will also involve strengthening research and education across disciplines, expanding opportunities for students, and building the partnerships and resources that will support the School’s future.

Reporting to the Executive Vice President and Provost, the Dean will provide leadership to propel the School of Data Science forward and enhance its national and global reputation. The Dean of the School of Data Science sits on the Dean’s Council with the deans of the University’s twelve schools, building relationships and collaborations, supporting the goals of the University, and strengthening the community.

The next Dean will serve as the School’s chief academic and administrative officer and a senior leader of the University. The Dean will elevate the School's profile, deepen its role across Grounds, and build trust across faculty, staff, and students. As the School continues to grow, the Dean will help ensure the School remains focused, well organized, and positioned to become a lasting national model for rigorous, responsible, and impactful data science.

About the UVA School of Data Science

The University of Virginia School of Data Science is the first standalone school of data science and UVA’s 12th and newest school. Founded in 2019, the School of Data Science is guided by common goals: to further discovery, share knowledge, and make a positive impact on society through collaborative, open, and responsible data science research and education.

Designed as a “school without walls,” the School of Data Science brings together faculty, students, and partners across disciplines to address complex challenges through data. Today, the School seeks to make that identity increasingly visible across Grounds, strengthening its connections with the rest of the University and playing a larger role in advancing data science as a foundation for responsible AI and understanding AI's societal implications.

The School of Data Science is fast-growing and interdisciplinary, with 56 faculty, 10 wage faculty, 51 staff, and 22 research staff working across the technical, computational, human, and societal dimensions of data science. The School offers undergraduate and graduate education programs, enrolling over 600 students in 2026.

Mission

In concert with other University schools, train a diverse workforce at the undergraduate, graduate, and postgraduate levels to be responsible practitioners and leaders in an increasingly data-driven society.
In collaboration with other schools, undertake leading-edge interdisciplinary, open research that is not likely to be undertaken in a single school and thereby catalyze research discovery through innovative data science methods, computational approaches, and interdisciplinary expertise.
Serve the University, the local community, the Commonwealth, the nation and the world by applying data science to seek the truth and maximize societal benefit.

Academic Growth

Since launching its B.S. in Data Science in fall 2024, the School of Data Science now offers programs from undergraduate through doctoral education. Data Science has also become UVA’s most popular minor, with more than 400 students enrolled. In 2026, the School introduced four residential M.S. concentrations in artificial intelligence, data visualization, genomics, and sports data science. The School is ranked #8 on Forbes’ list of “Best Online Data Science Master’s Degrees” and recognized as the best for Career Support.

Research with Real-World Impact

School of Data Science faculty apply rigorous, interdisciplinary data science to challenges across health, democracy, culture, environment, and business. Recent faculty-led projects reflect that breadth, spanning AI-enabled physics, biomedical data science, and responsible AI in medicine. In 2025, UVA was selected to help lead a $15M Department of Energy research center advancing AI-assisted physics simulations, a project co-led by a School of Data Science faculty member. Separately, NIH invested $2.7M to expand UVA’s Biomedical Data Science Innovation Lab and awarded $1M to support research developing more accountable, participatory AI systems in medicine.

Across UVA, School of Data Science faculty partner with the Biocomplexity Institute, National Security Data and Policy Institute, LaCross Institute for Ethical Artificial Intelligence in Business, School of Engineering and Applied Science, School of Medicine, Darden School of Business, and Frank Batten School of Leadership and Public Policy.

Investing in the School’s Next Stage

Recent investments are creating the infrastructure for the School of Data Science’s continued growth. In 2024, the School opened its 60,000-square-foot home on the Emmet-Ivy Corridor. In 2026, UVA approved a new School of Data Science Entrepreneurship Building. This 62,000-square-foot building, scheduled to open in 2029, will include classrooms, offices, and collaborative research spaces, as well as a front door for entrepreneurship at the University.

The University is also investing $102M in a new 53,000-square-foot Research Data Center to enable more ambitious computational research, including AI. Scheduled to open in late 2028 or early 2029, the facility will initially provide 4.5MW of capacity, with the ability to expand to 17MW.

Budget and Financial Resources

The School of Data Science has an FY2027 operating budget of approximately $34.3M. Its largest sources of operating revenue are tuition and fees ($16.1M), endowment distribution ($9M), and sponsored research ($3.8M).

Programs and Degree Offerings

B.S. in Data Science

An undergraduate degree that develops expertise in data analytics, systems, design, and ethics alongside critical thinking and responsible judgment to prepare students for careers and research in data science.

Minor in Data Science

An undergraduate program that introduces students to data analytics, engineering, design, and ethics to build foundational skills in data science.

M.S. in Data Science, Residential

A one-year, full-time graduate program that develops advanced skills in data analytics, machine learning, and computational methods through rigorous, applied learning to prepare students for professional careers in data science.

M.S. in Data Science, Online

A flexible, part-time graduate program that develops advanced skills in data analytics, machine learning, and computational methods and their responsible application to prepare working professionals for careers in data science.

Combination Degrees

An interdisciplinary graduate pathway that integrates advanced data science training with graduate studies in medicine, business, public policy, and the arts and sciences to support research across disciplines.

Ph.D. in Data Science

An interdisciplinary doctoral program that develops expertise in computational and mathematical methods to prepare scholars to conduct rigorous, original research and advance the field of data science.

Non-Degree Programs

A series of non-credit educational offerings that develop foundational skills in mathematics, programming, and data science to support continued learning and professional development.

Data Science Capstone

An experiential learning opportunity that enables students to apply data science methods and interdisciplinary problem-solving skills to real-world challenges through collaborative projects with external partners.

The Role and Responsibilities

Work with faculty through shared governance to envision the School’s next chapter in a way that builds on the School’s interdisciplinary identity. Position the School to help define the future of rigorous, responsible, and impactful data science through education, research, engagement, and public impact.
Guide the School through its next stage of growth, aligning academic ambition with enrollment strategy, program development, people, infrastructure, financial resources, and operating systems. Ensure that the School is seen as a leading and preeminent institution at all degree levels and for research.
Build organizational capacity for the School's next stage by developing people, strengthening administrative systems, creating clarity around priorities and decision-making, and supporting effective execution. Recruit, retain, develop, and support outstanding faculty and staff who can advance the School’s interdisciplinary teaching, research, and impact.
Drive research breakthroughs and societal impact, strengthening the research enterprise and enabling faculty to apply interdisciplinary data science to pressing challenges in health, climate, science, policy, and society.
Attract and develop a high-quality student cohort from the Commonwealth, nation, and world.
Ensure outstanding student outcomes on several levels: career and internship opportunities, satisfaction, and academically. Equally, ensure outstanding faculty research, teaching, and career advancement.
Position the School as a university-wide convener and partner in data science and AI, reinforcing the foundational role of data science in advancing responsible AI and bringing together technical, scientific, social science, humanities, policy, and professional perspectives across Grounds. Deepen collaboration across UVA’s schools, institutes, and centers.
Deepen the School’s connection to industry and emerging AI practice, ensuring that developments in the field inform research and curriculum.
Serve as the School's leading ambassador, spokesperson, and thought leader, articulating a compelling and inspiring vision to alumni, donors, and external partners about the School and the field of data science. Expand external partnerships, nationally and globally, with industry—including frontier AI labs and AI tooling providers—as well as alumni, donors, foundations, government, and community partners that support research, internships, capstones, career pathways, knowledge translation, and student outcomes.
Lead fundraising and revenue diversification efforts, securing philanthropic, sponsored research, and partnership resources that advance priorities and strengthen long-term financial sustainability. Build the resources needed to advance the School’s ambitions, including support for scholarships, faculty excellence, capital projects, and other strategic priorities.
Advance academic excellence and student preparation, ensuring programs remain rigorous, relevant, and responsive to technological change, workforce needs, enrollment opportunities, and student success while preparing graduates to exercise sound judgment and apply data science responsibly.

The Person

Pivotal Experience and Expertise

Candidates will be evaluated against the following criteria.

Intellectual Leadership and Research Excellence

A respected intellectual leader whose work is relevant to data science and who brings the breadth to lead a deeply interdisciplinary school. A champion for rigorous, high-impact research, responsible innovation, and the foundational role of data science in emerging technologies, including AI, with the academic credibility to inspire an accomplished faculty. Candidates from the academy should have a record of publication, teaching, service, and impact that meets the standards for appointment as a full professor with tenure at UVA. Candidates from outside the academy should be able to demonstrate appreciation for the importance of engaged research and an aptitude to advance impactful scholarship.

Ambassadorship and Field-Building Leadership

A big-picture thinker on the evolving field of data science, with a track record of innovation and inspiring others to mobilize behind a vision. Can translate that vision into a clear strategy for the School, articulate its distinctive contribution to the field, elevate its national and global reputation, and build support for it across a diverse set of stakeholders.

Enterprise Leadership and Operational Excellence

An experienced organizational leader and excellent manager who can guide a fast-growing school through its next stage of development. Brings the judgment to align people, priorities, operations, financial resources, enrollment, infrastructure, and systems while preserving agility and entrepreneurial energy. Proven ability to achieve excellence and attract top faculty, staff, and student talent. Strong financial acumen.

Stakeholder Engagement and Fundraising

A compelling ambassador with demonstrated ability to build durable relationships with alumni, donors, foundations, industry, government, and community partners. Can create the external relationships and resources needed for student opportunities, research impact, knowledge translation, and long-term sustainability.

Culture Impact

Traits the leader will model.

Relational and Community-Oriented

Is visible, approachable, and deeply engaged with faculty, staff, and students. Builds authentic relationships, communicates openly, and creates a strong sense of shared purpose.

Collaborative and Institutionally Minded

Builds trust across faculty, staff, students, University leadership, alumni, and partners while embracing the School of Data Science’s identity as a “School Without Walls.” Leads through collaboration and helps further the School’s cross-Grounds relationships. Works collaboratively with other senior leaders, including the deans of the other UVA schools, to advance University goals.

Entrepreneurial and Operationally Disciplined

Thrives in a young, fast-moving organization and is comfortable leading through ambiguity and change. Preserves the School of Data Science’s entrepreneurial energy and willingness to experiment while introducing the clarity and discipline needed for sustained growth.

Human-Centered and Values-Driven

Leads with integrity, intellectual rigor, sound judgment, and a commitment to responsible, ethical data science and AI in service of society. Fosters a people-centered environment where purpose, impact, and the public good remain central to decision-making.

Evidence- and Outcomes-Driven

Values rigorous inquiry, evidence, and a diversity of perspectives, always with a focus on outcomes. Is comfortable engaging in disagreement and complex questions, creating an environment where ideas can be challenged thoughtfully and people with differing viewpoints.

How to Apply

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The Stephenson Dean, School of Data Science

Edtech.com's Summary

The Stephenson Dean, School of Data Science Full Description

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