Data Scientist

Description

The Data Scientist role combines advanced statistical analysis, predictive modeling, and data visualization skills to drive data-driven insights that grow and optimize fundraising strategies for Operation Smile. The Data Scientist leverages donor behavior data to segment donors effectively, forecast fundraising outcomes, and enhance donor engagement and retention efforts. Through clear communication and strategic collaboration, the Data Scientist translates complex data insights into actionable recommendations, supporting informed decision-making and maximizing philanthropic impact.

Work Arrangement Notes:

Those living in the Hampton Roads area follow a hybrid work schedule and report to the office three days per week. Those outside of this area follow a remote work arrangement.

Essential Functions:

Predictive Modeling:

• Develop custom scripts and functions in R or Python to automate repetitive data analysis tasks, streamline workflow processes, and enhance the efficiency of fundraising operations.
• Use statistical techniques to score constituents based on data from the organization’s internal database. Combine wealth capacity data with generated affinity from predictive models to:
• Identify new compelling major gift prospects.
• Evaluate the currently managed prospects to find new, untapped opportunities.
• Utilize data visualization tools (e.g., Tableau, Power BI) to create compelling visual narratives that communicate fundraising trends, performance metrics, and strategic insights to internal stakeholders and external partners.

RFM Analysis:

• Score donors to summarize best givers based on a donor’s recency, frequency, and magnitude of giving.
• Identify high-value donor segments and provide insights to tailor fundraising strategies to maximize donor lifetime value and retention.

Year-over-Year Trend Analysis and Benchmarking:

• Compare fundraising performance over multiple time periods, sources, and gift funds to identify trends and anomalies that inform future fundraising performance.
• Collaborate with cross-functional teams to articulate data-driven fundraising strategies, develop actionable recommendations, and align analytical insights with organizational goals and priorities.

Requirements

• At least three years of statistical analysis or predictive modeling experience.
• Working knowledge of Microsoft Excel, PowerPoint, and data visualization software (i.e. PowerBI or Tableau).
• A bachelor’s degree or better in Statistics, Data Science, or Math. Comparable professional experience counts too!
• Experience using R or Python to perform statistical analyses and create interactive applications (Shiny, Streamlit)
• Experience with process automation using custom scripts and functions.
• Data visualization skills and the ability to use those skills to tell a compelling story.

Other helpful skills include:

• Experience with cloud-based data storage and computing services.
• Experience working for or with a non-profit organization.