Sr. Decision Scientist – Marketing and Enrollment Management

Join a team that transforms data into decisions. We use advanced analytics, AI, and experimentation to unlock opportunity, drive growth, and shape strategy across a mission-driven university.

Excelsior University is seeking a Decision Scientist who will leverage data science to drive strategic initiatives, improve operational efficiency, and achieve institutional goals. Reporting to the Director of Analytics, the decision scientist will collaborate closely with business partners in Marketing, Admissions, Advising, Student Financial Services, and the Office of the Registrar. The role will be responsible for using machine learning, predictive modeling, experimental design, and other analytical techniques to inform strategic decisions and identify opportunities for efficiency and growth. This role gives you the opportunity to lead innovative projects and support Excelsior’s mission of serving adult learners, with an emphasis on those historically underrepresented in higher education.

We believe work should fit your life, not the other way around. While it is preferred that team members be located in Albany, New York, or a nearby area, remote work options will be considered. Our hybrid schedule has you in the Albany office on Tuesdays and Wednesdays, with the flexibility to work from home on other days. Spend less time commuting and more time focusing on meaningful work or personal priorities. Core hours are 8:30 AM–5:00 PM, including a 1-hour lunch, for a 37.5-hour week.

Duties and Responsibilities include the following

• Use predictive and prescriptive analytical techniques to enable leadership to make informed decisions
• Apply demonstrated knowledge of data modeling, business analysis, and statistical analysis to design and evaluate drivers of growth and efficiency.
• Uses various data analytics tools to clean, manipulate, and transform data for analysis.
• Support projects and work with university leaders to identify assumptions for analytical tools...