Enrollment Data Scientist

Duties and Responsibilities

• Design predictive models to help educational institutions understand the factors that predict student application, enrollment, and retention
• Refine and shape data files with a focus on quality control to maximize their ability to answer research questions
• Work with clients and internal teams to ensure the accuracy of data sets and analyses
• Present findings to clients as needed through oral presentations, written reports, and slide decks
• Ask questions and work seamlessly with teammates
• Approach their work with positivity, enthusiasm, and passion

Knowledge/Skills/Abilities

• Strong interest in education, quantitative research, and statistical methods
• Strong skills in written and oral communication, organization, and collaborating effectively with a diverse team
• Proficiency in quantitative statistics packages like R, SPSS, SAS, or a similar language; R strongly preferred
• Effective communication and time management skills are required, as well as the ability to use/learn multiple technology platforms and switch between them on a regular basis

About the Role

For more than 30 years, Carnegie has been a leader and innovator in higher education marketing and enrollment strategy, offering groundbreaking services in the areas of Research, Strategy, Digital Marketing, Lead Generation, Slate Optimization, Student Search, Website Development, and Creative that generate authentic connections.

Qualifications

• Bachelor’s degree in Social Science, Mathematics, Statistics, Business, or another discipline that emphasizes the importance of data analysis required; master’s degree preferred
• 1–3 years of demonstrated experience in an analytical role within the field of higher education or an educational organization (e.g., Enrollment Management, Institutional Research, Admission, Financial Aid, Enrollment Marketing, Advancement, etc.) preferred
• Experience with multivariate regression and classification techniques such as multiple regression, logistic regression, or machine learning algorithms