The business problem is to support the strategic goals of University Advancement at Bucknell University by transforming data into actionable insights that guide decision-making across strategic insight that drives alumni engagement and philanthropic growth.
Requirements
- Proficiency in R or Python for statistical analysis and machine learning.
- Strong SQL skills and experience working with relational databases and data warehouses.
- Experience with at least one data visualization tool (e.g., Tableau, Power BI, ggplot2).
- Deep understanding of statistical modeling techniques and machine learning algorithms.
- Demonstrated experience applying data science and AI techniques to translate complex business questions into actionable insights—including data wrangling, visualization, modeling, and interpretation of results.
- Demonstrated experience building statistical and machine learning models such as generalized linear regression, hierarchical models, nonparametric models, regression trees, and random forests.
- Experience in a nonprofit, higher education, or fundraising environment.
Responsibilities
- Analyze constituent and revenue data to surface trends, gaps, and opportunities that inform planning, prospect pipeline development, and fundraising performance.
- Design and implement statistical models (e.g., regression, clustering, survival analysis, ARIMA) to understand donor behavior and forecast giving potential.
- Source and prepare structured and unstructured data from various systems (CRM, digital engagement platforms, survey tools) for analysis.
- Automate recurring analytics processes to enable scalable, real-time decision-making.
- Serves a strategic thought partner with Strategic Philanthropy and Marketing, Strategy and Outreach teams to apply predictive models and performance analyses that guide donor outreach, portfolio management, and solicitation timing.
- Proactively analyze behavioral, demographic, and historical data to identify high-potential alumni audiences and uncover untapped engagement opportunities or gaps in current strategy.
- Collaborate with colleagues across advancement to integrate data insights into goal setting, progress tracking, and program design.
Other
- Bachelor’s degree and four years of professional experience in data science or a related data-focused field.
- OR Master’s degree in analytics, data science, statistics, computer science, information systems, or a related field and two years of professional experience in data science or a related data-focused field.
- Strong verbal and written communication skills, with the ability to convey complex concepts in clear, accessible ways that builds understanding and inspires action among diverse audiences.
- Curiosity and creativity in exploring new approaches to donor engagement and philanthropic behavior.
- Must be authorized to work in the US at the time of submission of the application.
