Assistant Director, Learning Analytics

Posting Number

2026-15383

The Assistant Director of Learning Analytics provides strategic leadership for the university's learning data ecosystem to drive institutional data strategy. This role is responsible for the vision, development, and scalability of learning analytics products that translate complex datasets into actionable insights. By bridging the gap between technical infrastructure (such as the Unizin Data Platform) and academic mission, the Assistant Director ensures that analytical tools are ethically grounded, sustainable, and aligned with university goals for student success. They serve as a primary consultant to senior leadership and faculty, fostering a data-informed culture across a global campus.

Required Education:
Master's Degree focus in data science or related field

Preferred Education:
Doctoral Degree Data Science or related field

Required Experience:
7+ years in higher education and related experience developing learning analytics design plans, or equivalent combination of education and experience. Must include experience using various forms of Learning Analytics tools and processes to inform learning analytics design plans and design strategy, such as Social Networking Analytics (SNA), Natural Language Processing (NLP), Educational Data Mining (EDM), Predictive Analytics, Adaptive Analytics, and Multimodal Learning Analytics. Experience providing formal instruction, preferably at the college level. Experience developing surveys and conducting focus groups. Experience designing Educational Databases and Reporting Tools. Experience using data visualization software. Experience navigating Learning Management Systems (especially Sakai). Experience applying Psychometrics and Assessment. Experience leading the management of a portfolio of enterprise applications used to support teaching and learning in a higher education environment. Experience with service management frameworks (e.g. ITIL).

Preferred Experience:
5+ years Higher education with a focus on data science, management, mapping and enterprise systems. Experience supervising a team that supports technology services.

Required Skills, Knowledge and Abilities:
Knowledge of data warehousing technologies and data mining computational methods. Demonstrated ability to work with sensitive, personal or protected data. Knowledge of Higher Education Student Information Systems. Knowledge of data warehousing technologies and data mining computational methods.

Preferred Skills, Knowledge and Abilities:
Work deliverables and leadership will ultimately impact the quality of technology enhanced education for courses, departments and schools within the University.

In compliance with NYC's Pay Transparency Act, the annual base salary range for this position is USD $105,940.00 to USD $125,940.00. New York University considers factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience, education/training, key skills, internal peer equity, as well as, market and organizational considerations when extending an offer. This pay range represents base pay only and excludes any additional items such as incentives, bonuses, clinical compensation, or other items.

NYU aims to be among the greenest urban campuses in the country and carbon neutral by 2040. Learn more at nyu.edu/nyugreen.

NYU is an Equal Opportunity Employer and is committed to a policy of equal treatment and opportunity in every aspect of its recruitment and hiring process without regard to age, alienage, caregiver status, childbirth, citizenship status, color, creed, disability, domestic violence victim status, ethnicity, familial status, gender and/or gender identity or expression, marital status, military status, national origin, parental status, partnership status, predisposing genetic characteristics, pregnancy, race, religion, reproductive health decision making, sex, sexual orientation, unemployment status, veteran status, or any other legally protected basis. All interested persons are encouraged to apply at all levels.

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