Higher Education Data Scientist
A Higher Education Data Scientist analyzes complex institutional datasets to support strategic initiatives, improve student outcomes, and strengthen institutional effectiveness through advanced analytics and predictive modeling. This is a sample job description from Excelon Associates that you can adapt as a template for your own hire.
What does a Higher Education Data Scientist do?
A Higher Education Data Scientist plays a critical role analyzing complex datasets to support an institution's strategic initiatives, enhance student outcomes, and improve institutional effectiveness. The role brings a deep understanding of data analytics, machine learning, and predictive modeling to the higher education context.
The position leverages advanced analytics to drive decisions in academic administration, enrollment management, student retention, and institutional research, collecting, processing, and interpreting large educational datasets into actionable insight. It works closely with departments across the institution to address key challenges, within the higher education sector.
Institutional research is the analytics function that informs a college's decisions on enrollment, retention, and effectiveness. FERPA (Family Educational Rights and Privacy Act) is the U.S. law protecting student record privacy. SIS and LMS are the student information and learning management systems that hold much of the institution's data.
Who does the Data Scientist work with?
Key responsibilities of a Higher Education Data Scientist
- Collect, analyze, and interpret large educational datasets to identify trends and provide actionable insights for enrollment management, student retention, and institutional performance.
- Develop and deploy machine learning models to predict student outcomes, improve retention rates, and optimize resource allocation.
- Use predictive analytics to support student success initiatives and enhance academic planning.
- Create comprehensive data reports, dashboards, and visualizations to communicate findings to stakeholders clearly and actionably.
- Collaborate with academic and administrative departments to understand their data needs and provide tailored analytic solutions.
- Implement data governance policies and ensure compliance with privacy regulations such as FERPA.
- Stay current with the latest trends and technologies in higher education data science and apply innovative approaches to complex educational challenges.
What qualifications does the role require?
- Master's degree or PhD in data science, statistics, computer science, or a related field.
- Proven experience in higher education analytics or institutional research.
- Proficiency in data analytics tools such as Python, R, SQL, and Tableau, with strong knowledge of machine learning algorithms and predictive modeling.
- Familiarity with student information systems (SIS) and learning management systems (LMS), plus experience with data cleaning, ETL processes, and large datasets.
- Excellent communication skills, with the ability to present complex insights to non-technical stakeholders.
- Enrollment management or institutional research experience, understanding of FERPA, and knowledge of statistical modeling, data mining, and natural language processing (NLP).
- Experience with cloud platforms such as AWS or Google Cloud.
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Download the TemplateWhy is the Higher Education Data Scientist role important?
Institutions increasingly run on data. A Higher Education Data Scientist turns large, messy educational datasets into decisions that improve enrollment, retention, and student success, the outcomes that define whether an institution thrives.
Because the role sits between technical analytics and institutional strategy, the strongest candidates translate models into decisions non-technical leaders can act on, all while keeping the work compliant with FERPA and sound data governance. Insight that leaders cannot use, or that breaks privacy law, is no insight at all.
A hiring note from Excelon
The hard part of this hire is not finding a data scientist, it is finding one who understands higher education's data, its systems, its FERPA constraints, and the politics of institutional research. Through our higher education practice, we look for candidates who pair real modeling skill with sector fluency, since a strong technologist who does not know the domain tends to build models the institution cannot use.
Insight that leaders cannot act on, or that breaks privacy law, is no insight at all.
Related sample job descriptions
What does a Higher Education Data Scientist earn?
In Excelon Associates' higher education data scientist searches, offers have typically landed between $75,000 and $115,000 per year. The Bureau of Labor Statistics groups these roles under data scientists (SOC 15-2051), which carried a median annual wage of $112,590 in May 2024. Higher education hires below that cross-industry median, which technology and finance employers pull upward, and Excelon's range reflects what institutions actually pay against it.
Scope separates the analyst-plus roles from the real data science seats. Positions centered on institutional research reporting sit at the low end, while those building enrollment prediction models, retention early-alert systems, and production pipelines in Python and SQL reach the top. Cabinet visibility matters too; a data scientist presenting directly to enrollment leadership earns more than one buried in an IR office.
Higher Education Data Scientist: frequently asked questions
What does a Higher Education Data Scientist do?
A Higher Education Data Scientist analyzes complex institutional datasets to support strategic initiatives, student outcomes, and institutional effectiveness. The role builds machine learning and predictive models for enrollment, retention, and resource allocation, creates dashboards and reports, and partners with academic and administrative departments.
What qualifications does the role require?
This sample role requires a master's degree or PhD in data science, statistics, computer science, or a related field, experience in higher education analytics or institutional research, and proficiency with tools such as Python, R, SQL, and Tableau, plus machine learning and predictive modeling.
What is FERPA and why does it matter here?
FERPA, the Family Educational Rights and Privacy Act, is the U.S. law protecting the privacy of student education records. A Higher Education Data Scientist must implement data governance and ensure analytics work complies with FERPA.
What tools and systems does the role use?
Common tools include Python, R, SQL, and Tableau, along with machine learning frameworks. The role also works with student information systems (SIS) and learning management systems (LMS), and may use cloud platforms such as AWS or Google Cloud.
Why is this role important?
Institutions increasingly run on data. A Higher Education Data Scientist turns large educational datasets into decisions that improve enrollment, retention, and student success, while keeping that work compliant with privacy law.
How much does a Higher Education Data Scientist make?
In Excelon Associates' recent searches, higher education data scientist offers have typically landed between $75,000 and $115,000 per year. The BLS median for data scientists (SOC 15-2051) was $112,590 in May 2024, and scope of responsibility decides where an offer falls within the range.
Hiring a Higher Education Data Scientist?
Excelon Associates places data scientists, institutional research leaders, and analytics professionals at universities and colleges across the United States through our higher education recruitment practice. Retained executive search since 2007, headquartered in Asheville, NC, with offices in Boca Raton and Delray Beach, FL. The average Excelon search delivers a slate of 5 qualified candidates in 3 to 5 weeks, with 88 searches completed in the last 12 months.
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